From 475eb1311e706b1432a5c13f1a1b0585faef8155 Mon Sep 17 00:00:00 2001
From: jodie <liws18uk@yeah.net>
Date: Sat, 20 Jul 2019 11:17:58 +0100
Subject: [PATCH 01/32] Create .DS_Store

---
 .DS_Store | Bin 0 -> 6148 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 .DS_Store

diff --git a/.DS_Store b/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..d6d620b01f8b323578cb458998b15cf12e80a345
GIT binary patch
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From ddff60fc624bf7f0db3ad1eca87c8df608e03b47 Mon Sep 17 00:00:00 2001
From: jodie <liws18uk@yeah.net>
Date: Sat, 20 Jul 2019 15:09:24 +0100
Subject: [PATCH 02/32] Create client.py

add client
---
 Client_weishi/client.py | 0
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 Client_weishi/client.py

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
new file mode 100644
index 0000000..e69de29

From 640c52769449a34aaacf16e46500b6270004df38 Mon Sep 17 00:00:00 2001
From: jodie <liws18uk@yeah.net>
Date: Mon, 22 Jul 2019 11:44:00 +0100
Subject: [PATCH 03/32] add client

add client
---
 .DS_Store                                     |   Bin 6148 -> 6148 bytes
 Client_weishi/client.py                       |   135 +
 Client_weishi/face_detection.py               |    23 +
 Client_weishi/haarcascade_frontalface_alt.xml | 24350 +++++++++++
 .../haarcascade_frontalface_default.xml       | 33314 ++++++++++++++++
 5 files changed, 57822 insertions(+)
 create mode 100644 Client_weishi/face_detection.py
 create mode 100755 Client_weishi/haarcascade_frontalface_alt.xml
 create mode 100755 Client_weishi/haarcascade_frontalface_default.xml

diff --git a/.DS_Store b/.DS_Store
index d6d620b01f8b323578cb458998b15cf12e80a345..1993d5085c9aa4e350193e25f6114da7a2ff092d 100644
GIT binary patch
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index e69de29..cf7ab08 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -0,0 +1,135 @@
+#!/usr/bin/python
+#This is a MIRO ROS client for Python.
+
+# client Library 提供ROS编程的库（接口）
+import rospy
+# geometry_msgs provides messages for common geometric primitives such as points, vectors, and poses.
+# http://docs.ros.org/api/geometry_msgs/html/msg/TwistStamped.html
+from geometry_msgs.msg import TwistStamped
+
+import math
+import numpy as np
+import time
+import sys
+import os
+
+import cv2
+from cv_bridge import CvBridge, CvBridgeError
+from sensor_msgs.msg import CompressedImage
+from face_detection import *
+
+# The miro2 Python module provides constants and tools for working with MiRo from Python.
+# with PYTHONPATH=~/mdk/share/python:$PYTHONPATH
+import miro2 as miro
+
+
+################################################################
+
+def error(msg):
+    print(msg)
+    sys.exit(0)
+
+################################################################
+
+class controller:
+    def callback_caml(self, ros_image):
+        # ignore until active
+        if not self.active:
+            return
+
+        self.image_converter = CvBridge()
+        # convert compressed ROS image to raw CV image
+        image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
+
+        self.detected_faces = face_detection(image)
+
+
+
+    def loop(self):
+        # loop
+        while self.active and not rospy.core.is_shutdown():
+            if self.detected_faces != None:
+                cv2.imshow('image', self.detected_faces)
+                # https://www.jianshu.com/p/30c40d7ce5dc
+                cv2.waitKey(1)
+
+            if self.roi_color != None:
+                cv2.imshow('face', self.roi_color)
+                cv2.waitKey(1)
+
+            # yield
+            time.sleep(0.01)
+            self.t_now = self.t_now + 0.01
+
+        cv2.destroyAllWindows()
+
+
+# args 参数列表
+    def __init__(self, args):
+        # 注册和初始化node
+        rospy.init_node("client", anonymous=True)
+
+        # state
+        self.t_now = 0.0
+        self.active = False
+
+        # inputs
+        self.package = None
+        self.detected_faces = None
+        self.roi_color = None
+
+        # handle args
+        for arg in args:
+            # 在参数中找 = 并返回索引 如不含则返回-1
+            f = arg.find('=')
+            if f == -1:
+                key = arg
+                val = ""
+            else:
+                key = arg[:f]
+                val = arg[f + 1:]
+            if key == "pass":
+                pass
+            else:
+                error("argument not recognised \"" + arg + "\"")
+
+        # robot name
+        topic_base_name = "/" + os.getenv("MIRO_ROBOT_NAME")
+
+        # publish
+        # 定义topic --- 字符串
+        topic = topic_base_name + "/control/cmd_vel"
+        print("publish", topic)
+        # 返回publisher的对象，pub_cmd_vel是一个publisher,还没有真正的发布消息
+        # 同步 发收双方具有同频同相的同步时钟信号 在同步时钟的控制下逐位发送/接收
+        self.pub_cmd_vel = rospy.Publisher(topic, TwistStamped, queue_size=0)
+
+        # subscribe
+        # sensors/caml, Frames from the left eye camera (sample rate is variable, see control/command).
+        topicCamLeft = topic_base_name + "/sensors/caml/compressed"
+        print("subscribe", topicCamLeft)
+        # 异步 异步通信在发送字符时，发送端可以在任意时刻开始发送字符 接收端必须时刻做好接收的准备
+        self.sub_caml = rospy.Subscriber(topicCamLeft, CompressedImage, self.callback_caml, queue_size=1,
+                                         tcp_nodelay=True)
+
+
+        # wait for connect
+        print
+        "wait for connect..."
+        # 函数推迟调用线程的运行，可通过参数t指秒数，表示进程挂起的时间。
+        time.sleep(1)
+
+        # set to active
+        self.active = True
+
+
+
+
+
+if __name__ == "__main__":
+    main = controller(sys.argv[1:])
+    main.loop()
+
+
+
+
diff --git a/Client_weishi/face_detection.py b/Client_weishi/face_detection.py
new file mode 100644
index 0000000..2226fde
--- /dev/null
+++ b/Client_weishi/face_detection.py
@@ -0,0 +1,23 @@
+import cv2
+
+# face detection
+
+def face_detection(self, image):
+
+    self.detected_faces = image
+
+    face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+    if len(faces) > 0:
+        print(faces)
+        for (x, y, w, h) in faces:
+            cv2.rectangle(self.detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
+            face_x_coord = x + w / 2;
+            face_y_coord = y + h / 2;
+            roi_gray = gray[y:y + h, x:x + w]
+            self.roi_color = image[y:y + h, x:x + w]
+
+    return self.detected_faces
\ No newline at end of file
diff --git a/Client_weishi/haarcascade_frontalface_alt.xml b/Client_weishi/haarcascade_frontalface_alt.xml
new file mode 100755
index 0000000..ade4b21
--- /dev/null
+++ b/Client_weishi/haarcascade_frontalface_alt.xml
@@ -0,0 +1,24350 @@
+<?xml version="1.0"?>
+<!--
+    Stump-based 20x20 gentle adaboost frontal face detector.
+    Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<cascade type_id="opencv-cascade-classifier"><stageType>BOOST</stageType>
+  <featureType>HAAR</featureType>
+  <height>20</height>
+  <width>20</width>
+  <stageParams>
+    <maxWeakCount>213</maxWeakCount></stageParams>
+  <featureParams>
+    <maxCatCount>0</maxCatCount></featureParams>
+  <stageNum>22</stageNum>
+  <stages>
+    <_>
+      <maxWeakCount>3</maxWeakCount>
+      <stageThreshold>8.2268941402435303e-01</stageThreshold>
+      <weakClassifiers>
+        <_>
+          <internalNodes>
+            0 -1 0 4.0141958743333817e-03</internalNodes>
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+          <leafValues>
+            9.0049281716346741e-02 6.3748198747634888e-01</leafValues></_></weakClassifiers></_>
+    <_>
+      <maxWeakCount>16</maxWeakCount>
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diff --git a/Client_weishi/haarcascade_frontalface_default.xml b/Client_weishi/haarcascade_frontalface_default.xml
new file mode 100755
index 0000000..cbd1aa8
--- /dev/null
+++ b/Client_weishi/haarcascade_frontalface_default.xml
@@ -0,0 +1,33314 @@
+<?xml version="1.0"?>
+<!--
+    Stump-based 24x24 discrete(?) adaboost frontal face detector.
+    Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+  By downloading, copying, installing or using the software you agree to this license.
+  If you do not agree to this license, do not download, install,
+  copy or use the software.
+
+
+                        Intel License Agreement
+                For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+   * Redistribution's of source code must retain the above copyright notice,
+     this list of conditions and the following disclaimer.
+
+   * Redistribution's in binary form must reproduce the above copyright notice,
+     this list of conditions and the following disclaimer in the documentation
+     and/or other materials provided with the distribution.
+
+   * The name of Intel Corporation may not be used to endorse or promote products
+     derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
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From 16e3c8119cf00abb0f3210511ed51e41d4f25367 Mon Sep 17 00:00:00 2001
From: Weishi Li <43610109+jodie528@users.noreply.github.com>
Date: Sun, 28 Jul 2019 19:16:08 +0100
Subject: [PATCH 04/32] Update client.py

---
 Client_weishi/client.py | 6 ++++++
 1 file changed, 6 insertions(+)

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index cf7ab08..35a0f69 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -41,7 +41,9 @@ def callback_caml(self, ros_image):
         # convert compressed ROS image to raw CV image
         image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
 
+        # detect face and return the "face"
         self.detected_faces = face_detection(image)
+        
 
 
 
@@ -60,6 +62,10 @@ def loop(self):
             # yield
             time.sleep(0.01)
             self.t_now = self.t_now + 0.01
+            
+            # face recognition  run once/sec
+            self.is_primary = face_reco(self.detected_faces)
+            time.sleep(1000)
 
         cv2.destroyAllWindows()
 

From 847b73516313c3d06a256fd75861514e701c8c5a Mon Sep 17 00:00:00 2001
From: Weishi Li <43610109+jodie528@users.noreply.github.com>
Date: Mon, 29 Jul 2019 13:05:15 +0100
Subject: [PATCH 05/32] Delete client.py

---
 Client_weishi/client.py | 141 ----------------------------------------
 1 file changed, 141 deletions(-)
 delete mode 100644 Client_weishi/client.py

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
deleted file mode 100644
index 35a0f69..0000000
--- a/Client_weishi/client.py
+++ /dev/null
@@ -1,141 +0,0 @@
-#!/usr/bin/python
-#This is a MIRO ROS client for Python.
-
-# client Library 提供ROS编程的库（接口）
-import rospy
-# geometry_msgs provides messages for common geometric primitives such as points, vectors, and poses.
-# http://docs.ros.org/api/geometry_msgs/html/msg/TwistStamped.html
-from geometry_msgs.msg import TwistStamped
-
-import math
-import numpy as np
-import time
-import sys
-import os
-
-import cv2
-from cv_bridge import CvBridge, CvBridgeError
-from sensor_msgs.msg import CompressedImage
-from face_detection import *
-
-# The miro2 Python module provides constants and tools for working with MiRo from Python.
-# with PYTHONPATH=~/mdk/share/python:$PYTHONPATH
-import miro2 as miro
-
-
-################################################################
-
-def error(msg):
-    print(msg)
-    sys.exit(0)
-
-################################################################
-
-class controller:
-    def callback_caml(self, ros_image):
-        # ignore until active
-        if not self.active:
-            return
-
-        self.image_converter = CvBridge()
-        # convert compressed ROS image to raw CV image
-        image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
-
-        # detect face and return the "face"
-        self.detected_faces = face_detection(image)
-        
-
-
-
-    def loop(self):
-        # loop
-        while self.active and not rospy.core.is_shutdown():
-            if self.detected_faces != None:
-                cv2.imshow('image', self.detected_faces)
-                # https://www.jianshu.com/p/30c40d7ce5dc
-                cv2.waitKey(1)
-
-            if self.roi_color != None:
-                cv2.imshow('face', self.roi_color)
-                cv2.waitKey(1)
-
-            # yield
-            time.sleep(0.01)
-            self.t_now = self.t_now + 0.01
-            
-            # face recognition  run once/sec
-            self.is_primary = face_reco(self.detected_faces)
-            time.sleep(1000)
-
-        cv2.destroyAllWindows()
-
-
-# args 参数列表
-    def __init__(self, args):
-        # 注册和初始化node
-        rospy.init_node("client", anonymous=True)
-
-        # state
-        self.t_now = 0.0
-        self.active = False
-
-        # inputs
-        self.package = None
-        self.detected_faces = None
-        self.roi_color = None
-
-        # handle args
-        for arg in args:
-            # 在参数中找 = 并返回索引 如不含则返回-1
-            f = arg.find('=')
-            if f == -1:
-                key = arg
-                val = ""
-            else:
-                key = arg[:f]
-                val = arg[f + 1:]
-            if key == "pass":
-                pass
-            else:
-                error("argument not recognised \"" + arg + "\"")
-
-        # robot name
-        topic_base_name = "/" + os.getenv("MIRO_ROBOT_NAME")
-
-        # publish
-        # 定义topic --- 字符串
-        topic = topic_base_name + "/control/cmd_vel"
-        print("publish", topic)
-        # 返回publisher的对象，pub_cmd_vel是一个publisher,还没有真正的发布消息
-        # 同步 发收双方具有同频同相的同步时钟信号 在同步时钟的控制下逐位发送/接收
-        self.pub_cmd_vel = rospy.Publisher(topic, TwistStamped, queue_size=0)
-
-        # subscribe
-        # sensors/caml, Frames from the left eye camera (sample rate is variable, see control/command).
-        topicCamLeft = topic_base_name + "/sensors/caml/compressed"
-        print("subscribe", topicCamLeft)
-        # 异步 异步通信在发送字符时，发送端可以在任意时刻开始发送字符 接收端必须时刻做好接收的准备
-        self.sub_caml = rospy.Subscriber(topicCamLeft, CompressedImage, self.callback_caml, queue_size=1,
-                                         tcp_nodelay=True)
-
-
-        # wait for connect
-        print
-        "wait for connect..."
-        # 函数推迟调用线程的运行，可通过参数t指秒数，表示进程挂起的时间。
-        time.sleep(1)
-
-        # set to active
-        self.active = True
-
-
-
-
-
-if __name__ == "__main__":
-    main = controller(sys.argv[1:])
-    main.loop()
-
-
-
-

From 916d558707c4c606ad3df1252d88e328026dc72b Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Wed, 31 Jul 2019 12:24:25 +0100
Subject: [PATCH 06/32] add the client python file

---
 Client_weishi/client.py | 134 ++++++++++++++++++++++++++++++++++++++++
 1 file changed, 134 insertions(+)
 create mode 100644 Client_weishi/client.py

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
new file mode 100644
index 0000000..83b4eba
--- /dev/null
+++ b/Client_weishi/client.py
@@ -0,0 +1,134 @@
+#!/usr/bin/python
+#This is a MIRO ROS client for Python.
+
+import rospy
+# http://docs.ros.org/api/geometry_msgs/html/msg/TwistStamped.html
+from geometry_msgs.msg import TwistStamped
+
+import math
+import numpy as np
+import time
+import sys
+import os
+
+import cv2
+from cv_bridge import CvBridge, CvBridgeError
+from sensor_msgs.msg import CompressedImage
+from detect_primary_user import *
+
+# The miro2 Python module provides constants and tools for working with MiRo from Python.
+# with PYTHONPATH=~/mdk/share/python:$PYTHONPATH
+import miro2 as miro
+
+
+################################################################
+
+def error(msg):
+    print(msg)
+    sys.exit(0)
+
+################################################################
+
+class controller:
+    def callback_caml(self, ros_image):
+        # ignore until active
+        if not self.active:
+            return
+
+        self.image_converter = CvBridge()
+        # convert compressed ROS image to raw CV image
+        image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
+
+<<<<<<< HEAD
+        self.detected_faces, self.roi_color = face_detection(image)
+=======
+        # detect face and return the "face"
+        self.detected_faces = face_detection(image)
+        
+>>>>>>> 16e3c8119cf00abb0f3210511ed51e41d4f25367
+
+
+
+    def loop(self):
+        # loop
+        while self.active and not rospy.core.is_shutdown():
+            if self.detected_faces != None:
+                cv2.imshow('image', self.detected_faces)
+                # https://www.jianshu.com/p/30c40d7ce5dc
+                cv2.waitKey(1)
+
+            if self.roi_color != None:
+                cv2.imshow('face', self.roi_color)
+                cv2.waitKey(1)
+		
+            # yield
+            time.sleep(0.01)
+            self.t_now = self.t_now + 0.01
+            
+            # face recognition  run once/sec
+            self.is_primary = face_reco(self.detected_faces)
+            time.sleep(1000)
+
+        cv2.destroyAllWindows()
+
+
+    def __init__(self, args):
+        rospy.init_node("client", anonymous=True)
+
+        # state
+        self.t_now = 0.0
+        self.active = False
+
+        # inputs
+        self.package = None
+        self.detected_faces = None
+        self.roi_color = None
+
+        # handle args
+        for arg in args:
+            f = arg.find('=')
+            if f == -1:
+                key = arg
+                val = ""
+            else:
+                key = arg[:f]
+                val = arg[f + 1:]
+            if key == "pass":
+                pass
+            else:
+                error("argument not recognised \"" + arg + "\"")
+
+        # robot name
+        topic_base_name = "/" + os.getenv("MIRO_ROBOT_NAME")
+
+        # publish
+       # topic = topic_base_name + "/control/cmd_vel"
+       # print("publish", topic)
+       # self.pub_cmd_vel = rospy.Publisher(topic, TwistStamped, queue_size=0)
+
+        # subscribe
+        # sensors/caml, Frames from the left eye camera (sample rate is variable, see control/command).
+        topicCamLeft = topic_base_name + "/sensors/caml/compressed"
+        print("subscribe", topicCamLeft)
+        self.sub_caml = rospy.Subscriber(topicCamLeft, CompressedImage, self.callback_caml, queue_size=1,
+                                         tcp_nodelay=True)
+
+
+        # wait for connect
+        print "wait for connect..."
+        time.sleep(1)
+
+        # set to active
+        self.active = True
+
+
+
+
+
+if __name__ == "__main__":
+    main = controller(sys.argv[1:])
+    main.loop()
+
+
+
+

From bdfaab326fd93bcbb3aaef5adf828f0aaef48468 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Thu, 1 Aug 2019 15:34:28 +0100
Subject: [PATCH 07/32] add face re v1

---
 Client_weishi/client.py         | 10 ++++------
 Client_weishi/face_detection.py |  5 ++++-
 2 files changed, 8 insertions(+), 7 deletions(-)

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 83b4eba..5cc29b3 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -39,13 +39,9 @@ def callback_caml(self, ros_image):
         # convert compressed ROS image to raw CV image
         image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
 
-<<<<<<< HEAD
-        self.detected_faces, self.roi_color = face_detection(image)
-=======
         # detect face and return the "face"
         self.detected_faces = face_detection(image)
         
->>>>>>> 16e3c8119cf00abb0f3210511ed51e41d4f25367
 
 
 
@@ -54,8 +50,11 @@ def loop(self):
         while self.active and not rospy.core.is_shutdown():
             if self.detected_faces != None:
                 cv2.imshow('image', self.detected_faces)
-                # https://www.jianshu.com/p/30c40d7ce5dc
                 cv2.waitKey(1)
+                #face recognition
+                self.is_primary = face_recognition(self.detected_faces)
+
+                
 
             if self.roi_color != None:
                 cv2.imshow('face', self.roi_color)
@@ -66,7 +65,6 @@ def loop(self):
             self.t_now = self.t_now + 0.01
             
             # face recognition  run once/sec
-            self.is_primary = face_reco(self.detected_faces)
             time.sleep(1000)
 
         cv2.destroyAllWindows()
diff --git a/Client_weishi/face_detection.py b/Client_weishi/face_detection.py
index 2226fde..75a6ae7 100644
--- a/Client_weishi/face_detection.py
+++ b/Client_weishi/face_detection.py
@@ -20,4 +20,7 @@ def face_detection(self, image):
             roi_gray = gray[y:y + h, x:x + w]
             self.roi_color = image[y:y + h, x:x + w]
 
-    return self.detected_faces
\ No newline at end of file
+    return self.detected_faces
+
+def face_recognition(self, image):
+

From 572c58dfb1dcb2c0f36c31820f195f7fd6112081 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Fri, 2 Aug 2019 14:50:18 +0100
Subject: [PATCH 08/32] add test file

---
 Client_weishi/.client.py.swp                  | Bin 0 -> 12288 bytes
 .../miro2/core/node_detect_audio_engine.py    |   3 +
 test.py                                       |  77 ++++++++++++++++++
 3 files changed, 80 insertions(+)
 create mode 100644 Client_weishi/.client.py.swp
 create mode 100644 test.py

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
new file mode 100644
index 0000000000000000000000000000000000000000..c6c4b92280ece3c09f57f5126927f8882bd25129
GIT binary patch
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diff --git a/mdk/share/python/miro2/core/node_detect_audio_engine.py b/mdk/share/python/miro2/core/node_detect_audio_engine.py
index 842d7bf..472a582 100644
--- a/mdk/share/python/miro2/core/node_detect_audio_engine.py
+++ b/mdk/share/python/miro2/core/node_detect_audio_engine.py
@@ -135,6 +135,9 @@ def high_point(self, hn):
 		i_peak += L - L_max
 
 		# store
+
+		np.savetxt('tmp/wav',wav)
+		print("voice saved")
 		"""
 		np.savetxt('/tmp/wav', wav)
 		x = self.buf_abs_slow[:, hn-L:hn+L+1]
diff --git a/test.py b/test.py
new file mode 100644
index 0000000..34380ae
--- /dev/null
+++ b/test.py
@@ -0,0 +1,77 @@
+import boto3
+from PIL import Image
+from PIL import ImageDraw
+from PIL import ImageFont
+import io
+import os
+
+rekognition = boto3.client('rekognition', region_name='us-east-2')
+collectionId = 'primary_user'
+# create a collection
+
+# rekognition.create_collection(CollectionId=collectionId)
+path = '/home/miro/lib/miro_data/fr_lib/train'
+for r, d, f in os.walk(path):
+    print(r)
+    for file in f:
+        if file != '.DS_Store':
+            sourceFile = os.path.join(r, file)
+            imageSource = open(sourceFile, 'rb')
+            # adding faces to a Collection
+            response = rekognition.index_faces(Image={'Bytes': imageSource.read()}, ExternalImageId='jodie', CollectionId=collectionId)
+rekognition.describe_collection(CollectionId=collectionId)
+
+# test function: index_faces
+for faceRecord in response['FaceRecords']:
+    print('  Face ID:  ' + faceRecord['Face']['FaceId'])
+    print('  Location: {}'.format(faceRecord['Face']['BoundingBox']))
+
+print('create collection')
+
+# face detection
+imageSource=open('/home/miro/lib/miro_data/fr_lib/test/pic.jpg','rb')
+resp = rekognition.detect_faces(Image={'Bytes':imageSource.read()})
+all_faces = resp['FaceDetails']
+len(all_faces)
+
+
+image = Image.open("./lib_pic/lws/test_1.jpg")
+image_width,image_height  = image.size 
+
+print('re test pic')
+
+
+for face in all_faces:
+    box=face['BoundingBox']
+    x1 = box['Left'] * image_width
+    y1 = box['Top'] * image_height
+    x2 = x1 + box['Width'] * image_width
+    y2 = y1 + box['Height']  * image_height
+    
+    #get only face     
+    image_crop = image.crop((x1,y1,x2,y2))
+
+    #image convert to binary
+    stream = io.BytesIO()
+    image_crop.save(stream,format="JPEG")
+    image_crop_binary = stream.getvalue()
+    
+    #use image search faces in the Collection     
+    response = rekognition.search_faces_by_image(
+            CollectionId=collectionId,
+            Image={'Bytes':image_crop_binary}                                       
+            )
+
+    if len(response['FaceMatches']) > 0:
+        draw = ImageDraw.Draw(image)
+        points = (
+                    (x1,y1),
+                    (x2, y1),
+                    (x2, y2),
+                    (x1 , y2),
+                    (x1, y1)
+)
+        draw.line(points, fill='#00d400', width=2)
+        fnt = ImageFont.truetype('/Library/Fonts/Arial.ttf', 15)
+        draw.text((x1,y2),response['FaceMatches'][0]['Face']['ExternalImageId'], font=fnt, fill=(255, 255, 0))
+image.show()

From a2caf14e016cb81868ea7ffd23d1787b3e2bc16c Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Fri, 2 Aug 2019 14:51:57 +0100
Subject: [PATCH 09/32] m

---
 Client_weishi/.client.py.swp | Bin 12288 -> 0 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 Client_weishi/.client.py.swp

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
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From ac74a700c4f2572a81aa835c9b80aaff9bd4b86a Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Fri, 2 Aug 2019 17:09:08 +0100
Subject: [PATCH 10/32] add face test

---
 Client_weishi/.client.py.swp                    | Bin 0 -> 12288 bytes
 Client_weishi/.detect_primary_user.py.swo       | Bin 0 -> 12288 bytes
 Client_weishi/.detect_primary_user.py.swp       | Bin 0 -> 12288 bytes
 Client_weishi/client.py                         |  15 +++------------
 ...face_detection.py => detect_primary_user.py} |  13 +++++++------
 5 files changed, 10 insertions(+), 18 deletions(-)
 create mode 100644 Client_weishi/.client.py.swp
 create mode 100644 Client_weishi/.detect_primary_user.py.swo
 create mode 100644 Client_weishi/.detect_primary_user.py.swp
 rename Client_weishi/{face_detection.py => detect_primary_user.py} (60%)

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
new file mode 100644
index 0000000000000000000000000000000000000000..27216b6a1e1249c9f44b32752d158448097fbf32
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diff --git a/Client_weishi/.detect_primary_user.py.swo b/Client_weishi/.detect_primary_user.py.swo
new file mode 100644
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GIT binary patch
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diff --git a/Client_weishi/.detect_primary_user.py.swp b/Client_weishi/.detect_primary_user.py.swp
new file mode 100644
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 5cc29b3..b310624 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -40,10 +40,7 @@ def callback_caml(self, ros_image):
         image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
 
         # detect face and return the "face"
-        self.detected_faces = face_detection(image)
-        
-
-
+        self.detected_faces, self.roi_color = face_detection(image)
 
     def loop(self):
         # loop
@@ -52,9 +49,7 @@ def loop(self):
                 cv2.imshow('image', self.detected_faces)
                 cv2.waitKey(1)
                 #face recognition
-                self.is_primary = face_recognition(self.detected_faces)
-
-                
+                #self.is_primary = face_recognition(self.detected_faces)
 
             if self.roi_color != None:
                 cv2.imshow('face', self.roi_color)
@@ -65,7 +60,7 @@ def loop(self):
             self.t_now = self.t_now + 0.01
             
             # face recognition  run once/sec
-            time.sleep(1000)
+            #time.sleep(1000)
 
         cv2.destroyAllWindows()
 
@@ -119,10 +114,6 @@ def __init__(self, args):
         # set to active
         self.active = True
 
-
-
-
-
 if __name__ == "__main__":
     main = controller(sys.argv[1:])
     main.loop()
diff --git a/Client_weishi/face_detection.py b/Client_weishi/detect_primary_user.py
similarity index 60%
rename from Client_weishi/face_detection.py
rename to Client_weishi/detect_primary_user.py
index 75a6ae7..16e2e9b 100644
--- a/Client_weishi/face_detection.py
+++ b/Client_weishi/detect_primary_user.py
@@ -2,9 +2,10 @@
 
 # face detection
 
-def face_detection(self, image):
+def face_detection(image):
 
-    self.detected_faces = image
+    detected_faces = image
+    roi_color = None
 
     face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
 
@@ -14,13 +15,13 @@ def face_detection(self, image):
     if len(faces) > 0:
         print(faces)
         for (x, y, w, h) in faces:
-            cv2.rectangle(self.detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
+            cv2.rectangle(detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
             face_x_coord = x + w / 2;
             face_y_coord = y + h / 2;
             roi_gray = gray[y:y + h, x:x + w]
-            self.roi_color = image[y:y + h, x:x + w]
+            roi_color = image[y:y + h, x:x + w]
 
-    return self.detected_faces
+    return detected_faces, roi_color
 
-def face_recognition(self, image):
+#def face_recognition(image):
 

From 48510f3aea959785ecff9dbbee82889f8086a165 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Fri, 2 Aug 2019 18:01:45 +0100
Subject: [PATCH 11/32] add face re function

---
 Client_weishi/.client.py.swp              | Bin 12288 -> 0 bytes
 Client_weishi/.detect_primary_user.py.swo | Bin 12288 -> 0 bytes
 Client_weishi/.detect_primary_user.py.swp | Bin 12288 -> 16384 bytes
 Client_weishi/client.py                   |   6 ++
 Client_weishi/detect_primary_user.py      |  90 +++++++++++++++++++++-
 Client_weishi/user_pic.png                | Bin 0 -> 17243 bytes
 test.py                                   |  47 +++++------
 7 files changed, 113 insertions(+), 30 deletions(-)
 delete mode 100644 Client_weishi/.client.py.swp
 delete mode 100644 Client_weishi/.detect_primary_user.py.swo
 create mode 100644 Client_weishi/user_pic.png

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
deleted file mode 100644
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literal 0
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index b310624..38d814d 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -41,6 +41,8 @@ def callback_caml(self, ros_image):
 
         # detect face and return the "face"
         self.detected_faces, self.roi_color = face_detection(image)
+        
+
 
     def loop(self):
         # loop
@@ -51,8 +53,11 @@ def loop(self):
                 #face recognition
                 #self.is_primary = face_recognition(self.detected_faces)
 
+            # detect the face
             if self.roi_color != None:
+                save_face(self.roi_color)
                 cv2.imshow('face', self.roi_color)
+                face_recognition(self.roi_color)
                 cv2.waitKey(1)
 		
             # yield
@@ -67,6 +72,7 @@ def loop(self):
 
     def __init__(self, args):
         rospy.init_node("client", anonymous=True)
+       # init_rekognition()
 
         # state
         self.t_now = 0.0
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index 16e2e9b..6e24ec6 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -1,19 +1,23 @@
 import cv2
+import boto3
+import io
+import os
+from PIL import Image, ImageDraw, ImageFont
 
 # face detection
 
-def face_detection(image):
+def face_detection (image):
 
     detected_faces = image
     roi_color = None
 
+
     face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
 
     gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 
     faces = face_cascade.detectMultiScale(gray, 1.3, 5)
     if len(faces) > 0:
-        print(faces)
         for (x, y, w, h) in faces:
             cv2.rectangle(detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
             face_x_coord = x + w / 2;
@@ -23,5 +27,85 @@ def face_detection(image):
 
     return detected_faces, roi_color
 
-#def face_recognition(image):
+#save face
+def save_face(face):
+    cv2.imwrite('./user_pic.png', face)
+
+def init_rekognition():
+    rekognition = boto3.client('rekognition', region_name='us-east-2')
+    collectionId = 'primary_user'
+# create a collection
+#rekognition.create_collection(CollectionId=collectionId)
+    # path of the training pics library of the primary user
+    path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
+    path_fr = './user_pic.png'
+    username = 'MOM'
+
+def face_recognition(face):
+    rekognition = boto3.client('rekognition', region_name='us-east-2')
+    collectionId = 'primary_user'
+# create a collection
+#rekognition.create_collection(CollectionId=collectionId)
+    # path of the training pics library of the primary user
+    path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
+    path_fr = './user_pic.png'
+    username = 'MOM'
+    for r, d, f in os.walk(path):
+        for file in f:
+            if file != '.DS_Store':
+                sourceFile = os.path.join(r, file)
+                imageSource = open(sourceFile, 'rb')
+                # adding faces to a Collection
+                response = rekognition.index_faces(Image={'Bytes': imageSource.read()}, ExternalImageId=username, CollectionId=collectionId)
+   # rekognition.describe_collection(CollectionId=collectionId)
+
+# test function: index_faces
+# for faceRecord in response['FaceRecords']:
+#     print('  Face ID:  ' + faceRecord['Face']['FaceId'])
+#     print('  Location: {}'.format(faceRecord['Face']['BoundingBox']))
+
+# face search
+    imageSource=open(path_fr,'rb')
+    resp = rekognition.detect_faces(Image={'Bytes': imageSource.read()})
+    all_faces = resp['FaceDetails']
+    len(all_faces)
+
+
+    image = Image.open(path_fr)
+    image_width, image_height = image.size
+
+    for face in all_faces:
+        box = face['BoundingBox']
+        x1 = box['Left'] * image_width
+        y1 = box['Top'] * image_height
+        x2 = x1 + box['Width'] * image_width
+        y2 = y1 + box['Height'] * image_height
+    
+        #get only face     
+        image_crop = image.crop((x1, y1, x2, y2))
+
+        #image convert to binary
+        stream = io.BytesIO()
+        image.save(stream, format="JPEG")
+        image_crop_binary = stream.getvalue()
+    
+        #use image search faces in the Collection     
+        response = rekognition.search_faces_by_image(
+                CollectionId=collectionId,
+                Image={'Bytes': image_crop_binary}
+                )
 
+        if len(response['FaceMatches']) > 0:
+            draw = ImageDraw.Draw(image)
+            points = (
+                        (x1, y1),
+                        (x2, y1),
+                        (x2, y2),
+                        (x1, y2),
+                        (x1, y1)
+                    )
+            draw.line(points, fill='#00d400', width=2)
+            # fnt = ImageFont.truetype('/Library/Fonts/Arial.ttf', 15)
+            # draw.text((x1, y2), response['FaceMatches'][0]['Face']['ExternalImageId'], font=fnt, fill=(255, 255, 0))
+            draw.text((x1, y2), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
+    image.show()
diff --git a/Client_weishi/user_pic.png b/Client_weishi/user_pic.png
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HcmV?d00001

diff --git a/test.py b/test.py
index 34380ae..4f67862 100644
--- a/test.py
+++ b/test.py
@@ -1,18 +1,15 @@
 import boto3
-from PIL import Image
-from PIL import ImageDraw
-from PIL import ImageFont
 import io
+from PIL import Image, ImageDraw, ImageFont
 import os
 
 rekognition = boto3.client('rekognition', region_name='us-east-2')
 collectionId = 'primary_user'
 # create a collection
 
-# rekognition.create_collection(CollectionId=collectionId)
-path = '/home/miro/lib/miro_data/fr_lib/train'
+#rekognition.create_collection(CollectionId=collectionId)
+path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
 for r, d, f in os.walk(path):
-    print(r)
     for file in f:
         if file != '.DS_Store':
             sourceFile = os.path.join(r, file)
@@ -22,56 +19,52 @@
 rekognition.describe_collection(CollectionId=collectionId)
 
 # test function: index_faces
-for faceRecord in response['FaceRecords']:
-    print('  Face ID:  ' + faceRecord['Face']['FaceId'])
-    print('  Location: {}'.format(faceRecord['Face']['BoundingBox']))
-
-print('create collection')
+# for faceRecord in response['FaceRecords']:
+#     print('  Face ID:  ' + faceRecord['Face']['FaceId'])
+#     print('  Location: {}'.format(faceRecord['Face']['BoundingBox']))
 
 # face detection
-imageSource=open('/home/miro/lib/miro_data/fr_lib/test/pic.jpg','rb')
-resp = rekognition.detect_faces(Image={'Bytes':imageSource.read()})
+imageSource=open('/home/miro/jodie/MiRo/lib/fr_lib/test/pic.jpg','rb')
+resp = rekognition.detect_faces(Image={'Bytes': imageSource.read()})
 all_faces = resp['FaceDetails']
 len(all_faces)
 
 
-image = Image.open("./lib_pic/lws/test_1.jpg")
-image_width,image_height  = image.size 
-
-print('re test pic')
-
+image = Image.open("/home/miro/jodie/MiRo/lib/fr_lib/test/pic.jpg")
+image_width, image_height = image.size
 
 for face in all_faces:
-    box=face['BoundingBox']
+    box = face['BoundingBox']
     x1 = box['Left'] * image_width
     y1 = box['Top'] * image_height
     x2 = x1 + box['Width'] * image_width
-    y2 = y1 + box['Height']  * image_height
+    y2 = y1 + box['Height'] * image_height
     
     #get only face     
-    image_crop = image.crop((x1,y1,x2,y2))
+    image_crop = image.crop((x1, y1, x2, y2))
 
     #image convert to binary
     stream = io.BytesIO()
-    image_crop.save(stream,format="JPEG")
+    image.save(stream, format="JPEG")
     image_crop_binary = stream.getvalue()
     
     #use image search faces in the Collection     
     response = rekognition.search_faces_by_image(
             CollectionId=collectionId,
-            Image={'Bytes':image_crop_binary}                                       
+            Image={'Bytes': image_crop_binary}
             )
 
     if len(response['FaceMatches']) > 0:
         draw = ImageDraw.Draw(image)
         points = (
-                    (x1,y1),
+                    (x1, y1),
                     (x2, y1),
                     (x2, y2),
-                    (x1 , y2),
+                    (x1, y2),
                     (x1, y1)
 )
         draw.line(points, fill='#00d400', width=2)
-        fnt = ImageFont.truetype('/Library/Fonts/Arial.ttf', 15)
-        draw.text((x1,y2),response['FaceMatches'][0]['Face']['ExternalImageId'], font=fnt, fill=(255, 255, 0))
+        # fnt = ImageFont.truetype('/Library/Fonts/Arial.ttf', 15)
+        # draw.text((x1, y2), response['FaceMatches'][0]['Face']['ExternalImageId'], font=fnt, fill=(255, 255, 0))
+        draw.text((x1, y2), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
 image.show()

From 156d3f9b9a487892fc98d2897c1d60838b331d87 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Tue, 6 Aug 2019 17:52:23 +0100
Subject: [PATCH 12/32] face re v1

---
 Client_weishi/.client.py.swp                  | Bin 0 -> 20480 bytes
 ...ser.py.swp => .detect_primary_user.py.swo} | Bin 16384 -> 16384 bytes
 Client_weishi/client.py                       |  36 +++++++++++++++++-
 Client_weishi/detect_primary_user.py          |  26 ++++---------
 Client_weishi/user_pic.png                    | Bin 17243 -> 16744 bytes
 mdk/bin/shared/.client_gui.py.swp             | Bin 0 -> 16384 bytes
 mdk/bin/shared/.client_test.py.swp            | Bin 0 -> 20480 bytes
 mdk/share/python/miro2/utils/.kc.py.swp       | Bin 0 -> 16384 bytes
 8 files changed, 42 insertions(+), 20 deletions(-)
 create mode 100644 Client_weishi/.client.py.swp
 rename Client_weishi/{.detect_primary_user.py.swp => .detect_primary_user.py.swo} (58%)
 create mode 100644 mdk/bin/shared/.client_gui.py.swp
 create mode 100644 mdk/bin/shared/.client_test.py.swp
 create mode 100644 mdk/share/python/miro2/utils/.kc.py.swp

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
new file mode 100644
index 0000000000000000000000000000000000000000..840fa78933af5cbb1298dfc82c98c5f5c27648e5
GIT binary patch
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diff --git a/Client_weishi/.detect_primary_user.py.swp b/Client_weishi/.detect_primary_user.py.swo
similarity index 58%
rename from Client_weishi/.detect_primary_user.py.swp
rename to Client_weishi/.detect_primary_user.py.swo
index 88a528e527cdb0a7c3be71682ca71e7f5bbdb5a1..126008fe8b9962f934aa7d6521c73719fa36ce5a 100644
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 38d814d..5c4019c 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -31,6 +31,10 @@ def error(msg):
 
 class controller:
     def callback_caml(self, ros_image):
+
+        print(self.i, 'th callback_caml: ', time.time()-self.t)
+        self.i += 1
+
         # ignore until active
         if not self.active:
             return
@@ -57,7 +61,21 @@ def loop(self):
             if self.roi_color != None:
                 save_face(self.roi_color)
                 cv2.imshow('face', self.roi_color)
-                face_recognition(self.roi_color)
+
+                print(self.j, 'th face recognition: ')
+                st = time.time()
+                print('Start time: ', st-self.t)
+                self.j += 1
+                
+                face_recognition(self.roi_color, self.rekognition, self.collectionId, self.path, self.path_fr)
+                
+                et = time.time()
+                print('End time: ', et-self.t)
+                print('time of fr: ', et - st )
+               
+                # delay
+                #time.sleep(3000)
+
                 cv2.waitKey(1)
 		
             # yield
@@ -72,7 +90,11 @@ def loop(self):
 
     def __init__(self, args):
         rospy.init_node("client", anonymous=True)
-       # init_rekognition()
+        
+        # sim
+        self.t = time.time()
+        self.i = 0
+        self.j = 0
 
         # state
         self.t_now = 0.0
@@ -83,6 +105,16 @@ def __init__(self, args):
         self.detected_faces = None
         self.roi_color = None
 
+	# init aws rekognition
+	self.rekognition = boto3.client('rekognition', region_name='us-east-2')
+        self.collectionId = 'primary_user'
+        # create a collection
+        # rekognition.create_collection(CollectionId=collectionId)
+        # path of the training pics library of the primary user
+        self.path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
+        self.path_fr = './user_pic.png'
+        self.username = 'MOM'
+
         # handle args
         for arg in args:
             f = arg.find('=')
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index 6e24ec6..3e132ea 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -31,24 +31,15 @@ def face_detection (image):
 def save_face(face):
     cv2.imwrite('./user_pic.png', face)
 
-def init_rekognition():
-    rekognition = boto3.client('rekognition', region_name='us-east-2')
-    collectionId = 'primary_user'
-# create a collection
-#rekognition.create_collection(CollectionId=collectionId)
-    # path of the training pics library of the primary user
-    path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
-    path_fr = './user_pic.png'
-    username = 'MOM'
 
-def face_recognition(face):
-    rekognition = boto3.client('rekognition', region_name='us-east-2')
-    collectionId = 'primary_user'
-# create a collection
-#rekognition.create_collection(CollectionId=collectionId)
+def face_recognition(face, rekognition, collectionId, path, path_fr):
+    #rekognition = boto3.client('rekognition', region_name='us-east-2')
+    #collectionId = 'primary_user'
+    # create a collection
+    # rekognition.create_collection(CollectionId=collectionId)
     # path of the training pics library of the primary user
-    path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
-    path_fr = './user_pic.png'
+    #path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
+    #path_fr = './user_pic.png'
     username = 'MOM'
     for r, d, f in os.walk(path):
         for file in f:
@@ -57,7 +48,6 @@ def face_recognition(face):
                 imageSource = open(sourceFile, 'rb')
                 # adding faces to a Collection
                 response = rekognition.index_faces(Image={'Bytes': imageSource.read()}, ExternalImageId=username, CollectionId=collectionId)
-   # rekognition.describe_collection(CollectionId=collectionId)
 
 # test function: index_faces
 # for faceRecord in response['FaceRecords']:
@@ -107,5 +97,5 @@ def face_recognition(face):
             draw.line(points, fill='#00d400', width=2)
             # fnt = ImageFont.truetype('/Library/Fonts/Arial.ttf', 15)
             # draw.text((x1, y2), response['FaceMatches'][0]['Face']['ExternalImageId'], font=fnt, fill=(255, 255, 0))
-            draw.text((x1, y2), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
+            draw.text((x1, 0), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
     image.show()
diff --git a/Client_weishi/user_pic.png b/Client_weishi/user_pic.png
index a6764a2242d0597dde4743e0501028833b9734b9..adf5108d60cd8355605d7e73fe760858a3d9cd1a 100644
GIT binary patch
literal 16744
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diff --git a/mdk/share/python/miro2/utils/.kc.py.swp b/mdk/share/python/miro2/utils/.kc.py.swp
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From a3d7500790daaae86c1675a338d8d594ee330a84 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Tue, 13 Aug 2019 16:39:52 +0100
Subject: [PATCH 13/32] modify the face detection file

---
 Client_weishi/.client.py.swp              | Bin 20480 -> 16384 bytes
 Client_weishi/.detect_primary_user.py.swo | Bin 16384 -> 0 bytes
 Client_weishi/.detect_primary_user.py.swp | Bin 0 -> 12288 bytes
 Client_weishi/client.py                   |  16 +-
 Client_weishi/detect_primary_user.py      | 189 +++++++++++-----------
 Client_weishi/user_pic.png                | Bin 16744 -> 24310 bytes
 6 files changed, 103 insertions(+), 102 deletions(-)
 delete mode 100644 Client_weishi/.detect_primary_user.py.swo
 create mode 100644 Client_weishi/.detect_primary_user.py.swp

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
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diff --git a/Client_weishi/.detect_primary_user.py.swo b/Client_weishi/.detect_primary_user.py.swo
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 5c4019c..1129f33 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -31,6 +31,7 @@ def error(msg):
 
 class controller:
     def callback_caml(self, ros_image):
+        print('callback here')
 
         print(self.i, 'th callback_caml: ', time.time()-self.t)
         self.i += 1
@@ -49,6 +50,7 @@ def callback_caml(self, ros_image):
 
 
     def loop(self):
+        print('loop here')
         # loop
         while self.active and not rospy.core.is_shutdown():
             if self.detected_faces != None:
@@ -57,24 +59,18 @@ def loop(self):
                 #face recognition
                 #self.is_primary = face_recognition(self.detected_faces)
 
-            # detect the face
+            # have detected the face
             if self.roi_color != None:
-                save_face(self.roi_color)
-                cv2.imshow('face', self.roi_color)
+                #save_face(self.roi_color)
+                #cv2.imshow('face', self.roi_color)
 
-                print(self.j, 'th face recognition: ')
                 st = time.time()
-                print('Start time: ', st-self.t)
-                self.j += 1
-                
                 face_recognition(self.roi_color, self.rekognition, self.collectionId, self.path, self.path_fr)
-                
                 et = time.time()
-                print('End time: ', et-self.t)
                 print('time of fr: ', et - st )
                
                 # delay
-                #time.sleep(3000)
+                #time.sleep(3)
 
                 cv2.waitKey(1)
 		
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index 3e132ea..cb67095 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -6,96 +6,101 @@
 
 # face detection
 
-def face_detection (image):
-
-    detected_faces = image
-    roi_color = None
-
-
-    face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
-
-    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-
-    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
-    if len(faces) > 0:
-        for (x, y, w, h) in faces:
-            cv2.rectangle(detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
-            face_x_coord = x + w / 2;
-            face_y_coord = y + h / 2;
-            roi_gray = gray[y:y + h, x:x + w]
-            roi_color = image[y:y + h, x:x + w]
-
-    return detected_faces, roi_color
-
-#save face
-def save_face(face):
-    cv2.imwrite('./user_pic.png', face)
-
-
-def face_recognition(face, rekognition, collectionId, path, path_fr):
-    #rekognition = boto3.client('rekognition', region_name='us-east-2')
-    #collectionId = 'primary_user'
-    # create a collection
-    # rekognition.create_collection(CollectionId=collectionId)
-    # path of the training pics library of the primary user
-    #path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
-    #path_fr = './user_pic.png'
-    username = 'MOM'
-    for r, d, f in os.walk(path):
-        for file in f:
-            if file != '.DS_Store':
-                sourceFile = os.path.join(r, file)
-                imageSource = open(sourceFile, 'rb')
-                # adding faces to a Collection
-                response = rekognition.index_faces(Image={'Bytes': imageSource.read()}, ExternalImageId=username, CollectionId=collectionId)
-
-# test function: index_faces
-# for faceRecord in response['FaceRecords']:
-#     print('  Face ID:  ' + faceRecord['Face']['FaceId'])
-#     print('  Location: {}'.format(faceRecord['Face']['BoundingBox']))
-
-# face search
-    imageSource=open(path_fr,'rb')
-    resp = rekognition.detect_faces(Image={'Bytes': imageSource.read()})
-    all_faces = resp['FaceDetails']
-    len(all_faces)
-
-
-    image = Image.open(path_fr)
-    image_width, image_height = image.size
-
-    for face in all_faces:
-        box = face['BoundingBox']
-        x1 = box['Left'] * image_width
-        y1 = box['Top'] * image_height
-        x2 = x1 + box['Width'] * image_width
-        y2 = y1 + box['Height'] * image_height
-    
-        #get only face     
-        image_crop = image.crop((x1, y1, x2, y2))
-
-        #image convert to binary
-        stream = io.BytesIO()
-        image.save(stream, format="JPEG")
-        image_crop_binary = stream.getvalue()
-    
-        #use image search faces in the Collection     
-        response = rekognition.search_faces_by_image(
-                CollectionId=collectionId,
-                Image={'Bytes': image_crop_binary}
-                )
-
-        if len(response['FaceMatches']) > 0:
-            draw = ImageDraw.Draw(image)
-            points = (
-                        (x1, y1),
-                        (x2, y1),
-                        (x2, y2),
-                        (x1, y2),
-                        (x1, y1)
+class detect_primary_user:
+
+    def face_detection (image):
+
+        detected_faces = image
+        roi_color = None
+
+
+        face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
+
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+        faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+        if len(faces) > 0:
+            for (x, y, w, h) in faces:
+                cv2.rectangle(detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
+                face_x_coord = x + w / 2;
+                face_y_coord = y + h / 2;
+                roi_gray = gray[y:y + h, x:x + w]
+                roi_color = image[y:y + h, x:x + w]
+
+        return detected_faces, roi_color
+
+    #save face
+    def save_face(face):
+        cv2.imwrite('./user_pic.png', face)
+
+
+    def face_recognition(face, rekognition, collectionId, path, path_fr):
+        username = 'MOM'
+        for r, d, f in os.walk(path):
+            for file in f:
+                if file != '.DS_Store':
+                    sourceFile = os.path.join(r, file)
+                    imageSource = open(sourceFile, 'rb')
+                    # adding faces to a Collection
+                    response = rekognition.index_faces(Image={'Bytes': imageSource.read()}, ExternalImageId=username, CollectionId=collectionId)
+
+        # face search
+        imageSource=open(path_fr,'rb')
+        resp = rekognition.detect_faces(Image={'Bytes': imageSource.read()})
+        all_faces = resp['FaceDetails']
+        len(all_faces)
+
+
+        image = Image.open(path_fr)
+        image_width, image_height = image.size
+
+        for face in all_faces:
+
+            box = face['BoundingBox']
+            x1 = box['Left'] * image_width
+            y1 = box['Top'] * image_height
+            x2 = x1 + box['Width'] * image_width
+            y2 = y1 + box['Height'] * image_height
+
+        
+            #get only face     
+            image_crop = image.crop((x1, y1, x2, y2))
+
+            #image convert to binary
+            stream = io.BytesIO()
+            image.save(stream, format="JPEG")
+            image_crop_binary = stream.getvalue()
+        
+            #use image search faces in the Collection     
+            response = rekognition.search_faces_by_image(
+                    CollectionId=collectionId,
+                    Image={'Bytes': image_crop_binary}
                     )
-            draw.line(points, fill='#00d400', width=2)
-            # fnt = ImageFont.truetype('/Library/Fonts/Arial.ttf', 15)
-            # draw.text((x1, y2), response['FaceMatches'][0]['Face']['ExternalImageId'], font=fnt, fill=(255, 255, 0))
-            draw.text((x1, 0), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
-    image.show()
+
+            if len(response['FaceMatches']) > 0:
+                draw = ImageDraw.Draw(image)
+                points = (
+                            (x1, y1),
+                            (x2, y1),
+                            (x2, y2),
+                            (x1, y2),
+                            (x1, y1)
+                        )
+                draw.line(points, fill='#00d400', width=2)
+                draw.text((x1, 0), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
+        image.show()
+
+    def __init__ (self):
+        rekognition = boto3.client('rekognition', region_name='us-east-2')
+        collectionId = 'primary_user'
+        # create a collection
+        # rekognition.create_collection(CollectionId=collectionId)
+        # path of the training pics library of the primary user
+        path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
+        path_fr = './user_pic.png'
+
+
+
+
+
+
diff --git a/Client_weishi/user_pic.png b/Client_weishi/user_pic.png
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Ag#Z8m


From f4010f8889ab660fa1f89ff7341c406a81fb6578 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Tue, 13 Aug 2019 18:35:04 +0100
Subject: [PATCH 14/32] modify class

---
 Client_weishi/.client.py.swp              | Bin 16384 -> 20480 bytes
 Client_weishi/.detect_primary_user.py.swp | Bin 12288 -> 12288 bytes
 Client_weishi/client.py                   |  16 +++++++++-----
 Client_weishi/detect_primary_user.py      |  25 ++++++++++++----------
 Client_weishi/user_pic.png                | Bin 24310 -> 4909 bytes
 5 files changed, 25 insertions(+), 16 deletions(-)

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
index e8f325048e27afbf82b1cf9be8ce1a830509350c..8d80a5670c46fe59c53f31376c3e17ce5d196a32 100644
GIT binary patch
delta 1002
zcmc)IPe>F|9KiA4G`p^@Zo4j}h*{Ixx@*F^lwg0@sMv%cld?KQBCgJwmaeRdSclz1
z9y)ZWcQOd=nsvyj3?veQq)yc#NQfxvqKBe?B6a9H+1erRJ@_#1&u`v)^P68bt7XSE
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cL3M{Wsfud9dKC_+pW*GRg+!}|lz;2eFBgd00ssI2

delta 310
zcmZozz}V2hsE}k3=IN_ou4lpk1Of~UeK&(*lX<EbAC)sO<YpG-Ph6<7(PcF=Bg5to
z%tAc;Obqovbxa_|Ku|qdP(XaMhrka0i5nCqDX{P^2MVqS$pTFRN-7*?<K_k`=bn5^
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zu2(v^d5iJ{MsZGMh0MIn5{1O_VuhmA?EG{fCo?~9bGoWO>*Uq`p_6}V>20>uJ}v?P
DCAmic

diff --git a/Client_weishi/.detect_primary_user.py.swp b/Client_weishi/.detect_primary_user.py.swp
index 22249ac5571e737aab393ced754e3547c9f0b91b..3036fb52672a98ef13250a6541c690dca674f393 100644
GIT binary patch
delta 769
zcmZ9|OK1~O6vpwB)HK>Qod!W{5g8H@Q^rJXv4{v&s}Mny2#Sx=j+2Q7^J)^r6d?uO
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J*49|;<{x#!v)BLt

delta 645
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f?{VVi&v`+r=(|oaKhmS`*qf^_?1!d48^8G%D>{Q)

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 1129f33..6aff75b 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -45,7 +45,7 @@ def callback_caml(self, ros_image):
         image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
 
         # detect face and return the "face"
-        self.detected_faces, self.roi_color = face_detection(image)
+        self.detected_faces, self.roi_color = self.det_pri_user.face_detection(image)
         
 
 
@@ -61,11 +61,11 @@ def loop(self):
 
             # have detected the face
             if self.roi_color != None:
-                #save_face(self.roi_color)
-                #cv2.imshow('face', self.roi_color)
+                self.det_pri_user.save_face(self.roi_color)
+                cv2.imshow('face', self.roi_color)
 
                 st = time.time()
-                face_recognition(self.roi_color, self.rekognition, self.collectionId, self.path, self.path_fr)
+                self.det_pri_user.face_recognition(self.roi_color)
                 et = time.time()
                 print('time of fr: ', et - st )
                
@@ -101,7 +101,8 @@ def __init__(self, args):
         self.detected_faces = None
         self.roi_color = None
 
-	# init aws rekognition
+	'''
+        # init aws rekognition
 	self.rekognition = boto3.client('rekognition', region_name='us-east-2')
         self.collectionId = 'primary_user'
         # create a collection
@@ -110,6 +111,11 @@ def __init__(self, args):
         self.path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
         self.path_fr = './user_pic.png'
         self.username = 'MOM'
+        '''
+
+        # the object of detect_primary_user
+        self.det_pri_user = detect_primary_user()
+        
 
         # handle args
         for arg in args:
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index cb67095..d42da07 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -8,7 +8,7 @@
 
 class detect_primary_user:
 
-    def face_detection (image):
+    def face_detection (self, image):
 
         detected_faces = image
         roi_color = None
@@ -30,12 +30,15 @@ def face_detection (image):
         return detected_faces, roi_color
 
     #save face
-    def save_face(face):
-        cv2.imwrite('./user_pic.png', face)
+    def save_face(self, face):
+        cv2.imwrite(self.path_test, face)
 
 
-    def face_recognition(face, rekognition, collectionId, path, path_fr):
+    def face_recognition(self, face):
         username = 'MOM'
+        path = self.path_train
+        rekognition = self.rekognition
+        collectionId = self.collectionId
         for r, d, f in os.walk(path):
             for file in f:
                 if file != '.DS_Store':
@@ -45,13 +48,13 @@ def face_recognition(face, rekognition, collectionId, path, path_fr):
                     response = rekognition.index_faces(Image={'Bytes': imageSource.read()}, ExternalImageId=username, CollectionId=collectionId)
 
         # face search
-        imageSource=open(path_fr,'rb')
+        imageSource=open(self.path_test,'rb')
         resp = rekognition.detect_faces(Image={'Bytes': imageSource.read()})
         all_faces = resp['FaceDetails']
         len(all_faces)
 
 
-        image = Image.open(path_fr)
+        image = Image.open(self.path_test)
         image_width, image_height = image.size
 
         for face in all_faces:
@@ -91,13 +94,13 @@ def face_recognition(face, rekognition, collectionId, path, path_fr):
         image.show()
 
     def __init__ (self):
-        rekognition = boto3.client('rekognition', region_name='us-east-2')
-        collectionId = 'primary_user'
+        self.rekognition = boto3.client('rekognition', region_name='us-east-2')
+        self.collectionId = 'primary_user'
         # create a collection
         # rekognition.create_collection(CollectionId=collectionId)
-        # path of the training pics library of the primary user
-        path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
-        path_fr = './user_pic.png'
+        # self.path of the training pics library of the primary user
+        self.path_train = '/home/miro/jodie/MiRo/lib/fr_lib/train'
+        self.path_test = './user_pic.png'
 
 
 
diff --git a/Client_weishi/user_pic.png b/Client_weishi/user_pic.png
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GIT binary patch
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From f407fce3f44c8c2d0146f7c7fe5c04599245b0f0 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Thu, 15 Aug 2019 18:04:20 +0100
Subject: [PATCH 15/32] add joints

---
 Client_weishi/.client.py.swp              | Bin 20480 -> 0 bytes
 Client_weishi/.detect_primary_user.py.swp | Bin 12288 -> 0 bytes
 Client_weishi/client.py                   | 133 ++++++++++++++++------
 Client_weishi/detect_primary_user.py      |  79 +++++++------
 Client_weishi/user_pic.png                | Bin 4909 -> 449680 bytes
 5 files changed, 143 insertions(+), 69 deletions(-)
 delete mode 100644 Client_weishi/.client.py.swp
 delete mode 100644 Client_weishi/.detect_primary_user.py.swp

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
deleted file mode 100644
index 8d80a5670c46fe59c53f31376c3e17ce5d196a32..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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diff --git a/Client_weishi/.detect_primary_user.py.swp b/Client_weishi/.detect_primary_user.py.swp
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 6aff75b..004c0a0 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -13,7 +13,7 @@
 
 import cv2
 from cv_bridge import CvBridge, CvBridgeError
-from sensor_msgs.msg import CompressedImage
+from sensor_msgs.msg import CompressedImage, JointState
 from detect_primary_user import *
 
 # The miro2 Python module provides constants and tools for working with MiRo from Python.
@@ -30,11 +30,71 @@ def error(msg):
 ################################################################
 
 class controller:
-    def callback_caml(self, ros_image):
-        print('callback here')
 
-        print(self.i, 'th callback_caml: ', time.time()-self.t)
-        self.i += 1
+    def callback_package(self, msg):
+
+        # ignore until active
+        if not self.active:
+            return
+
+        # store
+        self.sensors = msg
+
+    def track( self, x_face, y_face, width, height ):
+
+        epsilon = 10.0
+        tilt, lift, yaw, pitch = range(4)
+        hf = y_face - height/2
+        df = x_face - width/2
+
+        #=====================test===============================
+        print('face_x: ', x_face, 'face_y: ' , y_face, 'image_width: ' , width, 'image_height: ' , height)
+        print('df: ', df, 'hf: ', hf)
+        #========================================================
+
+        # Horizon
+        if df > epsilon and self.kin_joints.position[yaw] > miro.constants.YAW_RAD_MIN:
+            # Move head to the right
+            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] - (df*miro.constants.YAW_RAD_MIN/width)
+            
+        elif df < -epsilon  and self.kin_joints.position[yaw] <  miro.constants.YAW_RAD_MAX:
+            # Move head to the left
+            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] + (df*miro.constants.YAW_RAD_MAX/width)
+
+        # Vertical
+        # if hf > epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
+        #     # Move head up
+        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] - math.radians(10.0)
+        #
+        # elif hf < -epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
+        #     # Move head down
+        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] + math.radians(10.0)
+
+        self.pub_kin.publish(self.kin_joints)
+        self.primary_detected = False
+        time.sleep(3)
+
+    def do_recognition(self):
+        # detect face and return the "face"
+        self.detected_faces, self.roi_color = self.det_pri_user.face_detection(self.image)
+
+        if self.roi_color != None:
+            # save ROI
+            self.det_pri_user.save_face(self.detected_faces)
+
+            # PRIMARY USER RECOGNITION, GET X,Y OF THE PRIMARY USER
+            st = time.time()
+            self.primary_detected, self.x_primary, self.y_primary, width, height = self.det_pri_user.face_recognition(
+                self.roi_color)
+            et = time.time()
+            print('time of fr: ', et - st)
+
+        self.image = None
+
+    def callback_caml(self, ros_image):
+        #print('callback here')
+        #print(self.i, 'th callback_caml: ', time.time()-self.t)
+        #self.i += 1
 
         # ignore until active
         if not self.active:
@@ -42,44 +102,39 @@ def callback_caml(self, ros_image):
 
         self.image_converter = CvBridge()
         # convert compressed ROS image to raw CV image
-        image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
+        self.image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
 
-        # detect face and return the "face"
-        self.detected_faces, self.roi_color = self.det_pri_user.face_detection(image)
-        
 
+    def reset(self):
+        self.kin_joints.position = [0.0, math.radians(34.0), 0.0, 0.0]
+        self.pub_kin.publish(self.kin_joints)
+        time.sleep(1)
 
     def loop(self):
-        print('loop here')
+        self.reset()
         # loop
         while self.active and not rospy.core.is_shutdown():
             if self.detected_faces != None:
-                cv2.imshow('image', self.detected_faces)
-                cv2.waitKey(1)
-                #face recognition
-                #self.is_primary = face_recognition(self.detected_faces)
+               cv2.imshow('detected_face', self.detected_faces)
+               cv2.waitKey(1)
 
-            # have detected the face
             if self.roi_color != None:
-                self.det_pri_user.save_face(self.roi_color)
                 cv2.imshow('face', self.roi_color)
+                cv2.waitKey(1)
+                
+            if self.image != None:
+                self.do_recognition()
+
+            if self.primary_detected == True:
+                self.track( self.x_primary, self.y_primary, 640, 360 )
 
-                st = time.time()
-                self.det_pri_user.face_recognition(self.roi_color)
-                et = time.time()
-                print('time of fr: ', et - st )
-               
-                # delay
-                #time.sleep(3)
 
-                cv2.waitKey(1)
-		
             # yield
             time.sleep(0.01)
             self.t_now = self.t_now + 0.01
             
             # face recognition  run once/sec
-            #time.sleep(1000)
+            #time.sleep(1)
 
         cv2.destroyAllWindows()
 
@@ -101,20 +156,11 @@ def __init__(self, args):
         self.detected_faces = None
         self.roi_color = None
 
-	'''
-        # init aws rekognition
-	self.rekognition = boto3.client('rekognition', region_name='us-east-2')
-        self.collectionId = 'primary_user'
-        # create a collection
-        # rekognition.create_collection(CollectionId=collectionId)
-        # path of the training pics library of the primary user
-        self.path = '/home/miro/jodie/MiRo/lib/fr_lib/train'
-        self.path_fr = './user_pic.png'
-        self.username = 'MOM'
-        '''
 
         # the object of detect_primary_user
         self.det_pri_user = detect_primary_user()
+        # create the diff images of user collection
+        self.det_pri_user.face_collection()
         
 
         # handle args
@@ -145,7 +191,18 @@ def __init__(self, args):
         print("subscribe", topicCamLeft)
         self.sub_caml = rospy.Subscriber(topicCamLeft, CompressedImage, self.callback_caml, queue_size=1,
                                          tcp_nodelay=True)
+        # subscribe
+        topic = topic_base_name + "/sensors/package"
+        print ("subscribe", topic)
+        self.sub_package = rospy.Subscriber(topic, miro.msg.sensors_package, self.callback_package)
+
+        # publish
+        topic = topic_base_name + "/control/kinematic_joints"
+        print ("publish", topic)
+        self.pub_kin = rospy.Publisher(topic, JointState, queue_size=0)
 
+        self.kin_joints = JointState()
+        self.kin_joints.name = ["tilt", "lift", "yaw", "pitch"]
 
         # wait for connect
         print "wait for connect..."
@@ -153,6 +210,8 @@ def __init__(self, args):
 
         # set to active
         self.active = True
+        self.primary_detected = False
+        self.image = None
 
 if __name__ == "__main__":
     main = controller(sys.argv[1:])
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index d42da07..2c6bfbb 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -3,6 +3,7 @@
 import io
 import os
 from PIL import Image, ImageDraw, ImageFont
+import matplotlib.pyplot as plt
 
 # face detection
 
@@ -13,28 +14,29 @@ def face_detection (self, image):
         detected_faces = image
         roi_color = None
 
-
         face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
 
         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 
         faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+
         if len(faces) > 0:
             for (x, y, w, h) in faces:
                 cv2.rectangle(detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
-                face_x_coord = x + w / 2;
-                face_y_coord = y + h / 2;
-                roi_gray = gray[y:y + h, x:x + w]
+                #face_x_coord = x + w / 2;
+                #face_y_coord = y + h / 2;
+                #roi_gray = gray[y:y + h, x:x + w]
                 roi_color = image[y:y + h, x:x + w]
 
         return detected_faces, roi_color
 
+
     #save face
     def save_face(self, face):
         cv2.imwrite(self.path_test, face)
 
 
-    def face_recognition(self, face):
+    def face_collection(self):
         username = 'MOM'
         path = self.path_train
         rekognition = self.rekognition
@@ -45,53 +47,66 @@ def face_recognition(self, face):
                     sourceFile = os.path.join(r, file)
                     imageSource = open(sourceFile, 'rb')
                     # adding faces to a Collection
-                    response = rekognition.index_faces(Image={'Bytes': imageSource.read()}, ExternalImageId=username, CollectionId=collectionId)
+                    response = rekognition.index_faces(
+                            Image={'Bytes': imageSource.read()}, 
+                            ExternalImageId=username, 
+                            CollectionId=collectionId)
+
 
+    def face_recognition(self, face):
         # face search
         imageSource=open(self.path_test,'rb')
-        resp = rekognition.detect_faces(Image={'Bytes': imageSource.read()})
-        all_faces = resp['FaceDetails']
-        len(all_faces)
-
-
+        resp = self.rekognition.detect_faces(Image={'Bytes': imageSource.read()})
         image = Image.open(self.path_test)
         image_width, image_height = image.size
-
+        all_faces = resp['FaceDetails']
+        
+        x_face = None
+        y_face = None
+        primary = False
+       
         for face in all_faces:
-
             box = face['BoundingBox']
             x1 = box['Left'] * image_width
             y1 = box['Top'] * image_height
             x2 = x1 + box['Width'] * image_width
             y2 = y1 + box['Height'] * image_height
 
-        
-            #get only face     
-            image_crop = image.crop((x1, y1, x2, y2))
-
             #image convert to binary
             stream = io.BytesIO()
             image.save(stream, format="JPEG")
-            image_crop_binary = stream.getvalue()
+            image_binary = stream.getvalue()
         
             #use image search faces in the Collection     
-            response = rekognition.search_faces_by_image(
-                    CollectionId=collectionId,
-                    Image={'Bytes': image_crop_binary}
+            response = self.rekognition.search_faces_by_image(
+                    CollectionId=self.collectionId,
+                    Image={'Bytes': image_binary}
                     )
 
             if len(response['FaceMatches']) > 0:
-                draw = ImageDraw.Draw(image)
-                points = (
-                            (x1, y1),
-                            (x2, y1),
-                            (x2, y2),
-                            (x1, y2),
-                            (x1, y1)
-                        )
-                draw.line(points, fill='#00d400', width=2)
-                draw.text((x1, 0), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
-        image.show()
+                #draw = ImageDraw.Draw(image)
+                x_face = (x1 + x2) / 2.0 
+                y_face = (y1 + y2) / 2.0
+                #plt.imshow(image)
+                #plt.text(x_face,y_face, 'PRIMARY USER')
+                #points = ( (x1, y1), (x2, y1), (x2, y2), (x1, y2), (x1, y1))
+                #draw.line(points, fill='#00d400', width=2)
+                #draw.text((x_face, y_face), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
+                primary = True
+
+               # plt.axis('off')
+               # mngr = plt.get_current_fig_manager()
+               # mngr.window.wm_geometry('+380+310')
+               # plt.pause(2)
+               # plt.ioff
+
+               # plt.clf()
+               # plt.close()
+
+
+        #image.show()
+
+        return primary, x_face, y_face, image_width, image_height
 
     def __init__ (self):
         self.rekognition = boto3.client('rekognition', region_name='us-east-2')
diff --git a/Client_weishi/user_pic.png b/Client_weishi/user_pic.png
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From 40f8eb0a83f40a12fd1409c1714b3ef8b67d8a0f Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Thu, 15 Aug 2019 21:01:31 +0100
Subject: [PATCH 16/32] direction correct

---
 Client_weishi/.client.py.swp              | Bin 0 -> 20480 bytes
 Client_weishi/.detect_primary_user.py.swp | Bin 0 -> 20480 bytes
 Client_weishi/client.py                   |  58 ++++++++++++++--------
 Client_weishi/detect_primary_user.py      |  11 ++--
 Client_weishi/user_pic.png                | Bin 449680 -> 7252 bytes
 5 files changed, 44 insertions(+), 25 deletions(-)
 create mode 100644 Client_weishi/.client.py.swp
 create mode 100644 Client_weishi/.detect_primary_user.py.swp

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 004c0a0..36001e6 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -48,27 +48,35 @@ def track( self, x_face, y_face, width, height ):
         df = x_face - width/2
 
         #=====================test===============================
-        print('face_x: ', x_face, 'face_y: ' , y_face, 'image_width: ' , width, 'image_height: ' , height)
+        print('============coordinate of face center=================')
+        print('face_x: ', x_face, 'face_y: ' , y_face)
         print('df: ', df, 'hf: ', hf)
+        print()
         #========================================================
 
         # Horizon
         if df > epsilon and self.kin_joints.position[yaw] > miro.constants.YAW_RAD_MIN:
             # Move head to the right
-            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] - (df*miro.constants.YAW_RAD_MIN/width)
-            
+            print('df > epsilon. move head to the right')
+            print('before rad: ', self.kin_joints.position[yaw])
+            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] + (df*miro.constants.YAW_RAD_MIN/width)
+            print('after rad: ', self.kin_joints.position[yaw])
+
         elif df < -epsilon  and self.kin_joints.position[yaw] <  miro.constants.YAW_RAD_MAX:
             # Move head to the left
-            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] + (df*miro.constants.YAW_RAD_MAX/width)
+            print('df < epsilon. move head to the left')
+            print('before rad: ', self.kin_joints.position[yaw])
+            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] - (df*miro.constants.YAW_RAD_MAX/width)
+            print('after rad: ', self.kin_joints.position[yaw])
 
         # Vertical
         # if hf > epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
         #     # Move head up
-        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] - math.radians(10.0)
+        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] + math.radians(10.0)
         #
         # elif hf < -epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
         #     # Move head down
-        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] + math.radians(10.0)
+        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] - math.radians(10.0)
 
         self.pub_kin.publish(self.kin_joints)
         self.primary_detected = False
@@ -76,18 +84,22 @@ def track( self, x_face, y_face, width, height ):
 
     def do_recognition(self):
         # detect face and return the "face"
-        self.detected_faces, self.roi_color = self.det_pri_user.face_detection(self.image)
+        st = time.time()
+        print('The current time: ', st)
+        self.detected_faces, self.roi_color, self.x_primary, self.y_primary = self.det_pri_user.face_detection(self.image)
+        et = time.time()
+        print('time of detection: ', et - st)
 
-        if self.roi_color != None:
+       # if self.roi_color != None:
             # save ROI
-            self.det_pri_user.save_face(self.detected_faces)
+           # self.det_pri_user.save_face(self.roi_color)
 
             # PRIMARY USER RECOGNITION, GET X,Y OF THE PRIMARY USER
-            st = time.time()
-            self.primary_detected, self.x_primary, self.y_primary, width, height = self.det_pri_user.face_recognition(
-                self.roi_color)
-            et = time.time()
-            print('time of fr: ', et - st)
+           # st = time.time()
+           # self.primary_detected, self.x_primary, self.y_primary, width, height = self.det_pri_user.face_recognition(
+           #     self.roi_color)
+           # et = time.time()
+           # print('time of fr: ', et - st)
 
         self.image = None
 
@@ -103,6 +115,16 @@ def callback_caml(self, ros_image):
         self.image_converter = CvBridge()
         # convert compressed ROS image to raw CV image
         self.image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
+            
+        if self.image != None:
+            self.do_recognition()
+
+        #if self.primary_detected == True:
+            #self.track( self.x_primary, self.y_primary, 640, 360 )
+
+        if self.x_primary != None:
+            self.track( self.x_primary, self.y_primary, 640, 360 )
+
 
 
     def reset(self):
@@ -122,13 +144,6 @@ def loop(self):
                 cv2.imshow('face', self.roi_color)
                 cv2.waitKey(1)
                 
-            if self.image != None:
-                self.do_recognition()
-
-            if self.primary_detected == True:
-                self.track( self.x_primary, self.y_primary, 640, 360 )
-
-
             # yield
             time.sleep(0.01)
             self.t_now = self.t_now + 0.01
@@ -155,6 +170,7 @@ def __init__(self, args):
         self.package = None
         self.detected_faces = None
         self.roi_color = None
+        self.x_primary = None
 
 
         # the object of detect_primary_user
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index 2c6bfbb..29915c8 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -13,7 +13,9 @@ def face_detection (self, image):
 
         detected_faces = image
         roi_color = None
-
+        face_x_coord = None
+        face_y_coord = None
+        
         face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
 
         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
@@ -23,12 +25,12 @@ def face_detection (self, image):
         if len(faces) > 0:
             for (x, y, w, h) in faces:
                 cv2.rectangle(detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
-                #face_x_coord = x + w / 2;
-                #face_y_coord = y + h / 2;
+                face_x_coord = x + w / 2;
+                face_y_coord = y + h / 2;
                 #roi_gray = gray[y:y + h, x:x + w]
                 roi_color = image[y:y + h, x:x + w]
 
-        return detected_faces, roi_color
+        return detected_faces, roi_color, face_x_coord, face_y_coord
 
 
     #save face
@@ -84,6 +86,7 @@ def face_recognition(self, face):
                     )
 
             if len(response['FaceMatches']) > 0:
+                print('=====FACE MATCH=====')
                 #draw = ImageDraw.Draw(image)
                 x_face = (x1 + x2) / 2.0 
                 y_face = (y1 + y2) / 2.0
diff --git a/Client_weishi/user_pic.png b/Client_weishi/user_pic.png
index 4b704c9b81bb795f73218ba5a9987be97cf9e03c..2dcaad8c78d4fca30ddf7035b2d1b2f49ef54c70 100644
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z*&cSqc43JeMg<eoy!_^>zB}uqEKiSGI!Tvl#02EI46a1?aH3qWc|>CK#A54FTT;^k
o?^Z|sEv3)PoR2Hi4?9j7zQ2z}G)tMgLf{ud$56Xc(?0V50MCRDoB#j-


From 30687e36fb009d5e9c6c3683e9ea30406579ca33 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Fri, 16 Aug 2019 20:28:34 +0100
Subject: [PATCH 17/32] direction up down

---
 Client_weishi/.client.py.swp | Bin 20480 -> 24576 bytes
 Client_weishi/client.py      |  64 +++++++++++++++++++++--------------
 2 files changed, 38 insertions(+), 26 deletions(-)

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
index fa3c59b028741b03c0ac70e274a96b22b2b4dc42..6743a94d09970d8bb449d975b9e1039ae650fb17 100644
GIT binary patch
delta 1758
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z90N0q+Y7d1G$az4Au$?>EY*Q~p{S66nvh6{nP6}vB#T6iMxu#|e(&raG<)GmKKGp4
z_T2lsx99x#A2aPgV^a3G+qShR-kLf=%M)VuX4_*g7XFdaULizRI2IipUo)}gL$f(e
z4Df>#<5x6ITJl!6rvGyyGLpSN*_)DmTC(p+_JRL=pPD=`OZL-=-Fb)1V@g_%afNZ?
zKqBs?TpGw&Da6@3g!mK_cm!_zvVwCo;rA>de!>_!u?|0E3ekrR@WO`61nxsSYK`!C
ziHC8c7MBP<i5IXF*HVQ~jFR>+_Mj1V*pP`Uyq8Zf3_oUxei6na9LEXyy!B^USCwBJ
zh$=DNAMJ>Q<KbweX|bs?xMo@wtCrlZ=riF+$66(zcf@pE&ZuQ_z?Pm;t;vT}m0^b5
zZnvg;T%n*#&e)5Jns?QP^l(QgE|eurQ<~(Uqu7`#Eown&D5x|ldiUONXEaiya1UJx
z=~_SuM0+E$!BJv11`AivJLNlekEv09YcEc1-c>L2)RKaK2dh`qwTeTw+RJjPHD|56
z#=Xv4ceiK#vMEbe|BsBtWb`eUv8UTeC||d)l;>=Z8t+jab>(KoW19adUX>hmm6of{
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delta 1420
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z2fvl!=rVaT>XV^pgt&od605ACXl<(HU)M8Nj#lT(d)4KVQu9e7)}&M=2V<Y0-5Msr
z9y50NF@k;Q!+MxFPTBY4AylFQK?Gp8#APZyfPLsgE9y{&D6%j~b@yhdQq{raZj_<~
yE}UgEqd0=?XuvjX#Rh0DOLOEoWxQ;WT)ZhyLhI7yCu4y%Rnw|j&(_9MHT4%|Oc4bD

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 36001e6..db1ac76 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -49,34 +49,39 @@ def track( self, x_face, y_face, width, height ):
 
         #=====================test===============================
         print('============coordinate of face center=================')
-        print('face_x: ', x_face, 'face_y: ' , y_face)
         print('df: ', df, 'hf: ', hf)
-        print()
         #========================================================
 
         # Horizon
-        if df > epsilon and self.kin_joints.position[yaw] > miro.constants.YAW_RAD_MIN:
-            # Move head to the right
-            print('df > epsilon. move head to the right')
-            print('before rad: ', self.kin_joints.position[yaw])
-            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] + (df*miro.constants.YAW_RAD_MIN/width)
-            print('after rad: ', self.kin_joints.position[yaw])
-
-        elif df < -epsilon  and self.kin_joints.position[yaw] <  miro.constants.YAW_RAD_MAX:
-            # Move head to the left
-            print('df < epsilon. move head to the left')
-            print('before rad: ', self.kin_joints.position[yaw])
-            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] - (df*miro.constants.YAW_RAD_MAX/width)
-            print('after rad: ', self.kin_joints.position[yaw])
-
-        # Vertical
-        # if hf > epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
-        #     # Move head up
-        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] + math.radians(10.0)
+        # if df > epsilon and self.kin_joints.position[yaw] > miro.constants.YAW_RAD_MIN:
+        #     # Move head to the right
+        #     print('df > epsilon. move head to the right')
+        #     print('before rad: ', self.kin_joints.position[yaw])
+        #     self.kin_joints.position[yaw] = self.kin_joints.position[yaw] + (df*miro.constants.YAW_RAD_MIN/width)
+        #     print('after rad: ', self.kin_joints.position[yaw])
         #
-        # elif hf < -epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
-        #     # Move head down
-        #     self.kin_joints.position[lift] = self.kin_joints.position[lift] - math.radians(10.0)
+        # elif df < -epsilon  and self.kin_joints.position[yaw] <  miro.constants.YAW_RAD_MAX:
+        #     # Move head to the left
+        #     print('df < epsilon. move head to the left')
+        #     print('before rad: ', self.kin_joints.position[yaw])
+        #     self.kin_joints.position[yaw] = self.kin_joints.position[yaw] - (df*miro.constants.YAW_RAD_MAX/width)
+        #     print('after rad: ', self.kin_joints.position[yaw])
+
+        #Vertical
+        print('==========================tracking============================')
+        if hf < -epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
+            # Move head up
+            print('hf > epsilon. move head up')
+            a = self.kin_joints.position[lift]
+            self.kin_joints.position[lift] = self.kin_joints.position[lift] + 3*hf*miro.constants.LIFT_RAD_MIN/height
+            print('after moving, degree: ', (self.kin_joints.position[lift]-a)/0.0174532)
+
+        elif hf > epsilon and self.kin_joints.position[lift] < miro.constants.LIFT_RAD_MAX:
+            # Move head down
+            print('hf < epsilon. move head down')
+            a = self.kin_joints.position[lift]
+            self.kin_joints.position[lift] = self.kin_joints.position[lift] + 3*hf*miro.constants.LIFT_RAD_MAX/height
+            print('after moving, degree: ', self.kin_joints.position[lift]-a)
 
         self.pub_kin.publish(self.kin_joints)
         self.primary_detected = False
@@ -85,11 +90,17 @@ def track( self, x_face, y_face, width, height ):
     def do_recognition(self):
         # detect face and return the "face"
         st = time.time()
+        print('============do recognition===========')
         print('The current time: ', st)
         self.detected_faces, self.roi_color, self.x_primary, self.y_primary = self.det_pri_user.face_detection(self.image)
         et = time.time()
         print('time of detection: ', et - st)
 
+        #----test-----
+        if self.roi_color != None :
+            print('Detected the face!!!!')
+        #-------------
+
        # if self.roi_color != None:
             # save ROI
            # self.det_pri_user.save_face(self.roi_color)
@@ -115,6 +126,7 @@ def callback_caml(self, ros_image):
         self.image_converter = CvBridge()
         # convert compressed ROS image to raw CV image
         self.image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
+        print('Receive a new image: ')
             
         if self.image != None:
             self.do_recognition()
@@ -136,9 +148,9 @@ def loop(self):
         self.reset()
         # loop
         while self.active and not rospy.core.is_shutdown():
-            if self.detected_faces != None:
-               cv2.imshow('detected_face', self.detected_faces)
-               cv2.waitKey(1)
+            #if self.detected_faces != None:
+            cv2.imshow('detected_face', self.detected_faces)
+            cv2.waitKey(1)
 
             if self.roi_color != None:
                 cv2.imshow('face', self.roi_color)

From 248143f4f813a50bc3fc6099f882c93b8b21134c Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Fri, 16 Aug 2019 20:58:15 +0100
Subject: [PATCH 18/32] direction up down 2

---
 Client_weishi/.client.py.swp | Bin 24576 -> 32768 bytes
 Client_weishi/client.py      |  33 +++++++++++++++++++++------------
 2 files changed, 21 insertions(+), 12 deletions(-)

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
index 6743a94d09970d8bb449d975b9e1039ae650fb17..8c4c0158bc8f2ed93a65df9256a28a33d96c4564 100644
GIT binary patch
delta 1474
zcmZY9Ur19?9Ki82-E6MrHYzG2Ju_)qVkwmm{YA8rR0<>Wq0IEAH*?h*Rt9bT6_KL4
z^&ruM&>x{B?S}LaWfqY^7Cn`b^hc<t%8crvf8V3i7#;ZR-gD2{@3Qmz{TA-Bgu^j%
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zG-E$1kdJv#DOAPMPwKjG1<lxi66C-JE54AzTR4XTtVTATkj5r#!4FcYhBQ-iypB**
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zkAny!gago#jIU1O;uU&u0~euVG5%2b0~4socih}UBep@cMjle}i?aWWduYXFG~gJH
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z;SB1q4h!LhYMowM;W2JvKk8A9EU3S`Zd&0k+K}hu!-D4=zu#tBtOK#8FK4A=byU@j
eP5vvtNUfzyRVe|jLeuLsSuXwB9ywBNeB&=~FZo&k

delta 751
zcmX}pUr1AN6u|Mbx#e7~dsoPUitg5*8DTCQtVG%fiHa6tB)!z_Dl1lOrZfvHw(KwU
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z9!l7OwOEFQfXGaMA&+u+jB~JX1R12U9R|Ku(-bB#hKINXg^M_jeaNC227WX2X}rcb
zUO~Y^Jv{j7XURX<$P6a%1Oqq&6Ir+$3*j4^`iu!&#T9fTiAF>*&$iy;Ec$R13(R{A
zHr(0Q;(yprSF4d?Kz&Mwo!(M97-`FO=JLHc!!nAw(?-5v9m_Qt@r};qz2z!@Ruj3P
hYFbwY?{eyQZ<@2Eb*E-0mi|psHlyBniyAif{{d*~hV}pe

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index db1ac76..2f4124f 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -48,8 +48,8 @@ def track( self, x_face, y_face, width, height ):
         df = x_face - width/2
 
         #=====================test===============================
-        print('============coordinate of face center=================')
-        print('df: ', df, 'hf: ', hf)
+        # print('============coordinate of face center=================')
+        # print('df: ', df, 'hf: ', hf)
         #========================================================
 
         # Horizon
@@ -68,20 +68,22 @@ def track( self, x_face, y_face, width, height ):
         #     print('after rad: ', self.kin_joints.position[yaw])
 
         #Vertical
-        print('==========================tracking============================')
+
+        # print()
+        # print('==========================tracking============================')
         if hf < -epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
             # Move head up
-            print('hf > epsilon. move head up')
-            a = self.kin_joints.position[lift]
+            # print('hf > epsilon. move head up')
+            # a = self.kin_joints.position[lift]
             self.kin_joints.position[lift] = self.kin_joints.position[lift] + 3*hf*miro.constants.LIFT_RAD_MIN/height
-            print('after moving, degree: ', (self.kin_joints.position[lift]-a)/0.0174532)
+            # print('after moving, degree: ', (self.kin_joints.position[lift]-a)/0.0174532)
 
         elif hf > epsilon and self.kin_joints.position[lift] < miro.constants.LIFT_RAD_MAX:
             # Move head down
-            print('hf < epsilon. move head down')
-            a = self.kin_joints.position[lift]
+            # print('hf < epsilon. move head down')
+            # a = self.kin_joints.position[lift]
             self.kin_joints.position[lift] = self.kin_joints.position[lift] + 3*hf*miro.constants.LIFT_RAD_MAX/height
-            print('after moving, degree: ', self.kin_joints.position[lift]-a)
+            # print('after moving, degree: ', self.kin_joints.position[lift]-a)
 
         self.pub_kin.publish(self.kin_joints)
         self.primary_detected = False
@@ -89,16 +91,18 @@ def track( self, x_face, y_face, width, height ):
 
     def do_recognition(self):
         # detect face and return the "face"
+        self.i += 1
         st = time.time()
+        print()
         print('============do recognition===========')
-        print('The current time: ', st)
+        print(self.i ,'th detection. The current time: ', st)
         self.detected_faces, self.roi_color, self.x_primary, self.y_primary = self.det_pri_user.face_detection(self.image)
         et = time.time()
         print('time of detection: ', et - st)
 
         #----test-----
         if self.roi_color != None :
-            print('Detected the face!!!!')
+            print(self.i ,'th detected the face!!!!')
         #-------------
 
        # if self.roi_color != None:
@@ -126,7 +130,12 @@ def callback_caml(self, ros_image):
         self.image_converter = CvBridge()
         # convert compressed ROS image to raw CV image
         self.image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
-        print('Receive a new image: ')
+        self.j += 1
+        
+        print()
+        print('**********************')
+        print(self.j , 'th receive a new image ')
+        print('**********************')
             
         if self.image != None:
             self.do_recognition()

From d23f000eeec59fc130da5cb7646dc4c472a20c12 Mon Sep 17 00:00:00 2001
From: jodie <liws18uk@yeah.net>
Date: Mon, 19 Aug 2019 00:13:44 +0100
Subject: [PATCH 19/32] not save test img

modify saving the test img to shorter time.
---
 Client_weishi/client.py              | 92 +++++++++++++++-------------
 Client_weishi/detect_primary_user.py | 14 +++--
 2 files changed, 61 insertions(+), 45 deletions(-)

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 2f4124f..8969cf9 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -10,7 +10,6 @@
 import time
 import sys
 import os
-
 import cv2
 from cv_bridge import CvBridge, CvBridgeError
 from sensor_msgs.msg import CompressedImage, JointState
@@ -42,6 +41,8 @@ def callback_package(self, msg):
 
     def track( self, x_face, y_face, width, height ):
 
+        st_track = time.time()
+
         epsilon = 10.0
         tilt, lift, yaw, pitch = range(4)
         hf = y_face - height/2
@@ -86,66 +87,57 @@ def track( self, x_face, y_face, width, height ):
             # print('after moving, degree: ', self.kin_joints.position[lift]-a)
 
         self.pub_kin.publish(self.kin_joints)
+
+        end_track = time.time()
+        print('time of tracking: ', end_track - st_track)
+
         self.primary_detected = False
-        time.sleep(3)
+        time.sleep(0.1)
+
+    def do_detection(self):
+
+        self.image_converter = CvBridge()
+        # convert compressed ROS image to raw CV image
+        self.image = self.image_converter.compressed_imgmsg_to_cv2(self.image, "bgr8")
 
-    def do_recognition(self):
         # detect face and return the "face"
         self.i += 1
         st = time.time()
         print()
         print('============do recognition===========')
-        print(self.i ,'th detection. The current time: ', st)
+        print(self.i, 'th detection. The current time: ', st)
         self.detected_faces, self.roi_color, self.x_primary, self.y_primary = self.det_pri_user.face_detection(self.image)
         et = time.time()
         print('time of detection: ', et - st)
 
-        #----test-----
-        if self.roi_color != None :
-            print(self.i ,'th detected the face!!!!')
-        #-------------
+        # ----test-----
+        if self.roi_color != None:
+            print(self.i, 'th detected the face!!!!')
+        # -------------
 
-       # if self.roi_color != None:
-            # save ROI
-           # self.det_pri_user.save_face(self.roi_color)
+        self.image = None
 
-            # PRIMARY USER RECOGNITION, GET X,Y OF THE PRIMARY USER
-           # st = time.time()
-           # self.primary_detected, self.x_primary, self.y_primary, width, height = self.det_pri_user.face_recognition(
-           #     self.roi_color)
-           # et = time.time()
-           # print('time of fr: ', et - st)
+    def do_recognition(self):
+        pass
 
-        self.image = None
+        # if self.roi_color != None:
+        # save ROI
+        # self.det_pri_user.save_face(self.roi_color)
+
+        # PRIMARY USER RECOGNITION, GET X,Y OF THE PRIMARY USER
+        # st = time.time()
+        # self.primary_detected, self.x_primary, self.y_primary = self.det_pri_user.face_recognition(
+        #     self.roi_color)
+        # et = time.time()
+        # print('time of fr: ', et - st)
 
-    def callback_caml(self, ros_image):
-        #print('callback here')
-        #print(self.i, 'th callback_caml: ', time.time()-self.t)
-        #self.i += 1
 
+    def callback_caml(self, ros_image):
         # ignore until active
         if not self.active:
             return
 
-        self.image_converter = CvBridge()
-        # convert compressed ROS image to raw CV image
-        self.image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
-        self.j += 1
-        
-        print()
-        print('**********************')
-        print(self.j , 'th receive a new image ')
-        print('**********************')
-            
-        if self.image != None:
-            self.do_recognition()
-
-        #if self.primary_detected == True:
-            #self.track( self.x_primary, self.y_primary, 640, 360 )
-
-        if self.x_primary != None:
-            self.track( self.x_primary, self.y_primary, 640, 360 )
-
+        self.image = ros_image
 
 
     def reset(self):
@@ -153,10 +145,24 @@ def reset(self):
         self.pub_kin.publish(self.kin_joints)
         time.sleep(1)
 
+
     def loop(self):
         self.reset()
         # loop
         while self.active and not rospy.core.is_shutdown():
+            # face detection
+            # 'Add new condition, do the recognition once of 100 frames'
+            if self.image != None:
+                self.do_detection()
+
+            # face recognition
+            # if self.primary_detected == True:
+            # self.track( self.x_primary, self.y_primary, 640, 360 )
+
+            if self.x_primary != None:
+                self.track(self.x_primary, self.y_primary, 640, 360)
+
+            # Show the frames and ROI
             #if self.detected_faces != None:
             cv2.imshow('detected_face', self.detected_faces)
             cv2.waitKey(1)
@@ -164,6 +170,10 @@ def loop(self):
             if self.roi_color != None:
                 cv2.imshow('face', self.roi_color)
                 cv2.waitKey(1)
+
+
+            # detect face 延迟很大之后tracking，所以不用每帧都做人脸检测并tracking。
+
                 
             # yield
             time.sleep(0.01)
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index 29915c8..42d0657 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -2,6 +2,7 @@
 import boto3
 import io
 import os
+import numpy as np
 from PIL import Image, ImageDraw, ImageFont
 import matplotlib.pyplot as plt
 
@@ -57,10 +58,15 @@ def face_collection(self):
 
     def face_recognition(self, face):
         # face search
-        imageSource=open(self.path_test,'rb')
-        resp = self.rekognition.detect_faces(Image={'Bytes': imageSource.read()})
-        image = Image.open(self.path_test)
+        success, encoded_image = cv2.imencode('.png', face)
+        face_bytes = encoded_image.tobytes()
+        resp = self.rekognition.detect_faces(Image={'Bytes': face_bytes})
+
+        array = cv2.cvtColor(np.array(face), cv2.COLOR_RGB2BGR)
+        image = Image.fromarray(array)
         image_width, image_height = image.size
+
+
         all_faces = resp['FaceDetails']
         
         x_face = None
@@ -109,7 +115,7 @@ def face_recognition(self, face):
 
         #image.show()
 
-        return primary, x_face, y_face, image_width, image_height
+        return primary, x_face, y_face
 
     def __init__ (self):
         self.rekognition = boto3.client('rekognition', region_name='us-east-2')

From 6d3e5e6e15822a6951e51660d55b275c58132bbb Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Wed, 21 Aug 2019 15:02:15 +0100
Subject: [PATCH 20/32] get close

---
 Client_weishi/.client.py.swp               | Bin 32768 -> 0 bytes
 Client_weishi/.detect_primary_user.py.swp  | Bin 20480 -> 0 bytes
 Client_weishi/client.py                    | 230 ++++++++++++++-------
 Client_weishi/detect_primary_user.py       | 115 +++++------
 mdk/bin/shared/.client_gui.py.swp          | Bin 16384 -> 0 bytes
 mdk/bin/shared/.client_test.py.swp         | Bin 20480 -> 0 bytes
 mdk/bin/shared/pca/0.jpg                   | Bin 0 -> 83183 bytes
 mdk/bin/shared/pca/1.jpg                   | Bin 0 -> 83171 bytes
 mdk/bin/shared/pca/10.jpg                  | Bin 0 -> 60392 bytes
 mdk/bin/shared/pca/11.jpg                  | Bin 0 -> 60688 bytes
 mdk/bin/shared/pca/12.jpg                  | Bin 0 -> 57556 bytes
 mdk/bin/shared/pca/13.jpg                  | Bin 0 -> 59569 bytes
 mdk/bin/shared/pca/14.jpg                  | Bin 0 -> 79669 bytes
 mdk/bin/shared/pca/15.jpg                  | Bin 0 -> 59623 bytes
 mdk/bin/shared/pca/16.jpg                  | Bin 0 -> 58159 bytes
 mdk/bin/shared/pca/17.jpg                  | Bin 0 -> 69840 bytes
 mdk/bin/shared/pca/18.jpg                  | Bin 0 -> 74784 bytes
 mdk/bin/shared/pca/19.jpg                  | Bin 0 -> 81077 bytes
 mdk/bin/shared/pca/2.jpg                   | Bin 0 -> 83229 bytes
 mdk/bin/shared/pca/3.jpg                   | Bin 0 -> 83342 bytes
 mdk/bin/shared/pca/4.jpg                   | Bin 0 -> 83149 bytes
 mdk/bin/shared/pca/5.jpg                   | Bin 0 -> 83342 bytes
 mdk/bin/shared/pca/6.jpg                   | Bin 0 -> 83293 bytes
 mdk/bin/shared/pca/7.jpg                   | Bin 0 -> 83128 bytes
 mdk/bin/shared/pca/8.jpg                   | Bin 0 -> 83146 bytes
 mdk/bin/shared/pca/9.jpg                   | Bin 0 -> 82847 bytes
 mdk/bin/shared/pca/pca.py                  | 196 ++++++++++++++++++
 mdk/bin/shared/pca/test.out                |  20 ++
 mdk/share/python/miro2/core/client_demo.py |   2 +-
 mdk/share/python/miro2/utils/.kc.py.swp    | Bin 16384 -> 0 bytes
 30 files changed, 425 insertions(+), 138 deletions(-)
 delete mode 100644 Client_weishi/.client.py.swp
 delete mode 100644 Client_weishi/.detect_primary_user.py.swp
 delete mode 100644 mdk/bin/shared/.client_gui.py.swp
 delete mode 100644 mdk/bin/shared/.client_test.py.swp
 create mode 100644 mdk/bin/shared/pca/0.jpg
 create mode 100644 mdk/bin/shared/pca/1.jpg
 create mode 100644 mdk/bin/shared/pca/10.jpg
 create mode 100644 mdk/bin/shared/pca/11.jpg
 create mode 100644 mdk/bin/shared/pca/12.jpg
 create mode 100644 mdk/bin/shared/pca/13.jpg
 create mode 100644 mdk/bin/shared/pca/14.jpg
 create mode 100644 mdk/bin/shared/pca/15.jpg
 create mode 100644 mdk/bin/shared/pca/16.jpg
 create mode 100644 mdk/bin/shared/pca/17.jpg
 create mode 100644 mdk/bin/shared/pca/18.jpg
 create mode 100644 mdk/bin/shared/pca/19.jpg
 create mode 100644 mdk/bin/shared/pca/2.jpg
 create mode 100644 mdk/bin/shared/pca/3.jpg
 create mode 100644 mdk/bin/shared/pca/4.jpg
 create mode 100644 mdk/bin/shared/pca/5.jpg
 create mode 100644 mdk/bin/shared/pca/6.jpg
 create mode 100644 mdk/bin/shared/pca/7.jpg
 create mode 100644 mdk/bin/shared/pca/8.jpg
 create mode 100644 mdk/bin/shared/pca/9.jpg
 create mode 100644 mdk/bin/shared/pca/pca.py
 create mode 100644 mdk/bin/shared/pca/test.out
 delete mode 100644 mdk/share/python/miro2/utils/.kc.py.swp

diff --git a/Client_weishi/.client.py.swp b/Client_weishi/.client.py.swp
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diff --git a/Client_weishi/.detect_primary_user.py.swp b/Client_weishi/.detect_primary_user.py.swp
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diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index 8969cf9..f4dda25 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -11,6 +11,7 @@
 import sys
 import os
 import cv2
+import datetime
 from cv_bridge import CvBridge, CvBridgeError
 from sensor_msgs.msg import CompressedImage, JointState
 from detect_primary_user import *
@@ -39,14 +40,16 @@ def callback_package(self, msg):
         # store
         self.sensors = msg
 
-    def track( self, x_face, y_face, width, height ):
+    def track(self):
 
         st_track = time.time()
 
         epsilon = 10.0
         tilt, lift, yaw, pitch = range(4)
-        hf = y_face - height/2
-        df = x_face - width/2
+
+
+        hf = self.y_primary - self.image_height/2
+        df = self.x_primary - self.image_width/2
 
         #=====================test===============================
         # print('============coordinate of face center=================')
@@ -54,45 +57,42 @@ def track( self, x_face, y_face, width, height ):
         #========================================================
 
         # Horizon
-        # if df > epsilon and self.kin_joints.position[yaw] > miro.constants.YAW_RAD_MIN:
-        #     # Move head to the right
-        #     print('df > epsilon. move head to the right')
-        #     print('before rad: ', self.kin_joints.position[yaw])
-        #     self.kin_joints.position[yaw] = self.kin_joints.position[yaw] + (df*miro.constants.YAW_RAD_MIN/width)
-        #     print('after rad: ', self.kin_joints.position[yaw])
-        #
-        # elif df < -epsilon  and self.kin_joints.position[yaw] <  miro.constants.YAW_RAD_MAX:
-        #     # Move head to the left
-        #     print('df < epsilon. move head to the left')
-        #     print('before rad: ', self.kin_joints.position[yaw])
-        #     self.kin_joints.position[yaw] = self.kin_joints.position[yaw] - (df*miro.constants.YAW_RAD_MAX/width)
-        #     print('after rad: ', self.kin_joints.position[yaw])
+        if df > epsilon and self.kin_joints.position[yaw] > miro.constants.YAW_RAD_MIN:
+            # Move head to the right
+            # print('df =  ', df, '  move head to the right')
+            # b = self.kin_joints.position[yaw]
+            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] + (0.7*df*miro.constants.YAW_RAD_MIN/self.image_width)
+            # print('after rad: ', (self.kin_joints.position[yaw]-b)/0.0174532)
+
+        elif df < -epsilon and self.kin_joints.position[yaw] < miro.constants.YAW_RAD_MAX:
+            # Move head to the left
+            # print('df < epsilon. move head to the left')
+            # b = self.kin_joints.position[yaw]
+            self.kin_joints.position[yaw] = self.kin_joints.position[yaw] - (0.7*df*miro.constants.YAW_RAD_MAX/self.image_width)
+            # print('after rad: ', (self.kin_joints.position[yaw]-b)/0.0174532)
+
+        # Vertical
 
-        #Vertical
-
-        # print()
-        # print('==========================tracking============================')
         if hf < -epsilon and self.kin_joints.position[lift] > miro.constants.LIFT_RAD_MIN:
             # Move head up
             # print('hf > epsilon. move head up')
             # a = self.kin_joints.position[lift]
-            self.kin_joints.position[lift] = self.kin_joints.position[lift] + 3*hf*miro.constants.LIFT_RAD_MIN/height
+            self.kin_joints.position[lift] = self.kin_joints.position[lift] + hf*miro.constants.LIFT_RAD_MIN/self.image_height
             # print('after moving, degree: ', (self.kin_joints.position[lift]-a)/0.0174532)
 
         elif hf > epsilon and self.kin_joints.position[lift] < miro.constants.LIFT_RAD_MAX:
             # Move head down
-            # print('hf < epsilon. move head down')
-            # a = self.kin_joints.position[lift]
-            self.kin_joints.position[lift] = self.kin_joints.position[lift] + 3*hf*miro.constants.LIFT_RAD_MAX/height
-            # print('after moving, degree: ', self.kin_joints.position[lift]-a)
+            print('hf < epsilon. move head down')
+            a = self.kin_joints.position[lift]
+            self.kin_joints.position[lift] = self.kin_joints.position[lift] + hf*miro.constants.LIFT_RAD_MAX/self.image_height
+            print('after moving, degree: ', self.kin_joints.position[lift]-a)
 
         self.pub_kin.publish(self.kin_joints)
 
         end_track = time.time()
-        print('time of tracking: ', end_track - st_track)
+        print('******************time of tracking: ', end_track - st_track)
 
-        self.primary_detected = False
-        time.sleep(0.1)
+        time.sleep(0.3)
 
     def do_detection(self):
 
@@ -101,36 +101,29 @@ def do_detection(self):
         self.image = self.image_converter.compressed_imgmsg_to_cv2(self.image, "bgr8")
 
         # detect face and return the "face"
-        self.i += 1
-        st = time.time()
-        print()
-        print('============do recognition===========')
-        print(self.i, 'th detection. The current time: ', st)
-        self.detected_faces, self.roi_color, self.x_primary, self.y_primary = self.det_pri_user.face_detection(self.image)
-        et = time.time()
-        print('time of detection: ', et - st)
-
-        # ----test-----
-        if self.roi_color != None:
-            print(self.i, 'th detected the face!!!!')
-        # -------------
+        # st = time.time()
+        self.detected_faces, self.faces = self.det_pri_user.face_detection(self.image)
+        # et = time.time()
+        # print('******************time of detection: ', et - st)
 
         self.image = None
 
     def do_recognition(self):
-        pass
-
-        # if self.roi_color != None:
-        # save ROI
-        # self.det_pri_user.save_face(self.roi_color)
 
         # PRIMARY USER RECOGNITION, GET X,Y OF THE PRIMARY USER
-        # st = time.time()
-        # self.primary_detected, self.x_primary, self.y_primary = self.det_pri_user.face_recognition(
-        #     self.roi_color)
-        # et = time.time()
-        # print('time of fr: ', et - st)
+        st = time.time()
+        # self.faces is the dictionary of faces include roi & coordinate of face center
+        self.primary_detected, self.face_user = self.det_pri_user.face_recognition(self.faces)
+        et = time.time()
+        print('******************time of recognition: ', et - st)
 
+        # x = self.face_user[0]
+        # y = self.face_user[1]
+        # w = self.face_user[2]
+        # h = self.face_user[3]
+        if self.face_user != []:
+            self.x_primary = self.face_user[0] + self.face_user[2]/2
+            self.y_primary = self.face_user[1] + self.face_user[3]/2
 
     def callback_caml(self, ros_image):
         # ignore until active
@@ -139,11 +132,94 @@ def callback_caml(self, ros_image):
 
         self.image = ros_image
 
-
     def reset(self):
         self.kin_joints.position = [0.0, math.radians(34.0), 0.0, 0.0]
         self.pub_kin.publish(self.kin_joints)
-        time.sleep(1)
+        time.sleep(0.1)
+
+    def get_face_distance(self, wf, hf):
+        d = 0.0
+        area_face = wf * hf
+        area_image = 640 * 360
+        # print ('&&&&&  face width  &&&&&    ', wf)
+        # print ('&&&&&  face height &&&&&    ', hf)
+        d = (area_face * 1.0) / area_image
+
+        return d
+
+    def move(self, wheel_speed):
+
+        # Convert to command velocity
+        (dr, dtheta) = miro.utils.wheel_speed2cmd_vel(wheel_speed)
+
+        # Set velocity values
+        self.velocity.twist.linear.x = dr
+        self.velocity.twist.angular.z = dtheta
+
+        self.pub_cmd_vel.publish(self.velocity)
+
+    def miro_approach(self):
+        tilt, lift, yaw, pitch = range(4)
+        if self.kin_joints.position[yaw] < -(20*0.0174532):
+            # move right
+            print('@@@@@@', self.kin_joints.position[yaw]/0.0174532)
+            print('@@@@@@move right')
+            self.run_sec('R')
+        elif self.kin_joints.position[yaw] > (20*0.0174532):
+            # move left
+            print('@@@@@@', self.kin_joints.position[yaw]/0.0174532)
+            print('@@@@@@move left')
+            self.run_sec('L')
+        else:
+            # move forward
+            print('@@@@@@move forward')
+            self.run_sec('U')
+        time.sleep(2)
+
+
+        print('@@@@@@after running for 0.2s')
+
+        # wheel_speed = [1.0, 1.0]
+        #
+        # self.do_detection()
+        # if self.faces != {}:
+        #     self.do_recognition()
+        #     if self.primary_detected == True:
+        #         # get close to user
+        #         d = self.get_face_distance(self.face_user[2], self.face_user[3])
+        #         while d > 0.05:
+        #             print('loop distance: ', d)
+        #             self.move(wheel_speed)
+        #             self.do_detection()
+        #             if self.faces != {}:
+        #                 self.do_recognition()
+        #                 if self.primary_detected == True:
+        #                     # get close to user
+        #                     d = self.get_face_distance(self.face_user[2], self.face_user[3])
+        # time.sleep(1)
+
+    # miro go straight for 0.1s
+    def run_sec(self, direction):
+
+        if direction == 'R':
+            wheel_speed = [0.2, 0.0]
+        elif direction == 'L':
+            wheel_speed = [0.0, 0.2]
+        elif direction == 'U':
+            wheel_speed = [0.2, 0.2]
+
+        start = datetime.datetime.now()
+
+        while True:
+            end = datetime.datetime.now()
+
+            if(end - start).microseconds > 200000:
+                wheel_speed0 = [0.0, 0.0]
+                self.move(wheel_speed0)
+                break
+            else:
+                self.move(wheel_speed)
+
 
 
     def loop(self):
@@ -155,24 +231,29 @@ def loop(self):
             if self.image != None:
                 self.do_detection()
 
-            # face recognition
-            # if self.primary_detected == True:
-            # self.track( self.x_primary, self.y_primary, 640, 360 )
-
-            if self.x_primary != None:
-                self.track(self.x_primary, self.y_primary, 640, 360)
+            # track primary user
+            if self.faces != {}:
+                self.do_recognition()
+                if self.primary_detected == True:
+                    self.track()
+                    # get close to user
+                    distance = self.get_face_distance(self.face_user[2], self.face_user[3])
+                    print('&&&&&  distance  &&&&&    ', distance)
+                    if distance < 0.02:
+                        self.miro_approach()
+
+            # track any face
+            # if self.x_primary != None:
+            #     self.track(self.x_primary, self.y_primary, 640, 360)
 
             # Show the frames and ROI
-            #if self.detected_faces != None:
-            cv2.imshow('detected_face', self.detected_faces)
-            cv2.waitKey(1)
-
-            if self.roi_color != None:
-                cv2.imshow('face', self.roi_color)
+            if self.detected_faces != None:
+                cv2.imshow('detected_face', self.detected_faces)
                 cv2.waitKey(1)
 
-
-            # detect face 延迟很大之后tracking，所以不用每帧都做人脸检测并tracking。
+            # if self.roi_color != None:
+            #     cv2.imshow('face', self.roi_color)
+            #     cv2.waitKey(1)
 
                 
             # yield
@@ -200,9 +281,16 @@ def __init__(self, args):
         # inputs
         self.package = None
         self.detected_faces = None
-        self.roi_color = None
+        # self.roi_color = None
+        self.faces = {}
+        self.face_user = []
         self.x_primary = None
+        self.y_primary = None
+        self.primary_detected = False
+        self.image_width = 640
+        self.image_height = 360
 
+        self.velocity = TwistStamped()
 
         # the object of detect_primary_user
         self.det_pri_user = detect_primary_user()
@@ -228,9 +316,9 @@ def __init__(self, args):
         topic_base_name = "/" + os.getenv("MIRO_ROBOT_NAME")
 
         # publish
-       # topic = topic_base_name + "/control/cmd_vel"
-       # print("publish", topic)
-       # self.pub_cmd_vel = rospy.Publisher(topic, TwistStamped, queue_size=0)
+        topic = topic_base_name + "/control/cmd_vel"
+        print("publish", topic)
+        self.pub_cmd_vel = rospy.Publisher(topic, TwistStamped, queue_size=0)
 
         # subscribe
         # sensors/caml, Frames from the left eye camera (sample rate is variable, see control/command).
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index 42d0657..b8ecdc1 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -7,7 +7,6 @@
 import matplotlib.pyplot as plt
 
 # face detection
-
 class detect_primary_user:
 
     def face_detection (self, image):
@@ -16,6 +15,7 @@ def face_detection (self, image):
         roi_color = None
         face_x_coord = None
         face_y_coord = None
+        dic_faces = {}
         
         face_cascade = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
 
@@ -25,18 +25,17 @@ def face_detection (self, image):
 
         if len(faces) > 0:
             for (x, y, w, h) in faces:
+                # index of face
+                face = 0
+
                 cv2.rectangle(detected_faces, (x, y), (x + w, y + h), (255, 0, 0), 2)
-                face_x_coord = x + w / 2;
-                face_y_coord = y + h / 2;
-                #roi_gray = gray[y:y + h, x:x + w]
+                # face_x_coord = x + w / 2
+                # face_y_coord = y + h / 2
                 roi_color = image[y:y + h, x:x + w]
+                dic_faces[face] = [roi_color, [x, y, w, h]]
+                face += 1
 
-        return detected_faces, roi_color, face_x_coord, face_y_coord
-
-
-    #save face
-    def save_face(self, face):
-        cv2.imwrite(self.path_test, face)
+        return detected_faces, dic_faces
 
 
     def face_collection(self):
@@ -50,72 +49,57 @@ def face_collection(self):
                     sourceFile = os.path.join(r, file)
                     imageSource = open(sourceFile, 'rb')
                     # adding faces to a Collection
-                    response = rekognition.index_faces(
+                    rekognition.index_faces(
                             Image={'Bytes': imageSource.read()}, 
                             ExternalImageId=username, 
                             CollectionId=collectionId)
 
 
-    def face_recognition(self, face):
-        # face search
-        success, encoded_image = cv2.imencode('.png', face)
-        face_bytes = encoded_image.tobytes()
-        resp = self.rekognition.detect_faces(Image={'Bytes': face_bytes})
-
-        array = cv2.cvtColor(np.array(face), cv2.COLOR_RGB2BGR)
-        image = Image.fromarray(array)
-        image_width, image_height = image.size
-
-
-        all_faces = resp['FaceDetails']
-        
-        x_face = None
-        y_face = None
+    def face_recognition(self, dic_faces):
         primary = False
-       
-        for face in all_faces:
-            box = face['BoundingBox']
-            x1 = box['Left'] * image_width
-            y1 = box['Top'] * image_height
-            x2 = x1 + box['Width'] * image_width
-            y2 = y1 + box['Height'] * image_height
+        face_user = []
 
+        for key, value in dic_faces.items():
+            face = value[0]
+
+            array = cv2.cvtColor(np.array(face), cv2.COLOR_RGB2BGR)
+            image = Image.fromarray(array)
             #image convert to binary
             stream = io.BytesIO()
             image.save(stream, format="JPEG")
             image_binary = stream.getvalue()
-        
-            #use image search faces in the Collection     
-            response = self.rekognition.search_faces_by_image(
-                    CollectionId=self.collectionId,
-                    Image={'Bytes': image_binary}
-                    )
-
-            if len(response['FaceMatches']) > 0:
-                print('=====FACE MATCH=====')
-                #draw = ImageDraw.Draw(image)
-                x_face = (x1 + x2) / 2.0 
-                y_face = (y1 + y2) / 2.0
-                #plt.imshow(image)
-                #plt.text(x_face,y_face, 'PRIMARY USER')
-                #points = ( (x1, y1), (x2, y1), (x2, y2), (x1, y2), (x1, y1))
-                #draw.line(points, fill='#00d400', width=2)
-                #draw.text((x_face, y_face), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
-                primary = True
-
-               # plt.axis('off')
-               # mngr = plt.get_current_fig_manager()
-               # mngr.window.wm_geometry('+380+310')
-               # plt.pause(2)
-               # plt.ioff
-
-               # plt.clf()
-               # plt.close()
-
-
-        #image.show()
-
-        return primary, x_face, y_face
+            #use image search faces in the Collection
+            try:
+                response = self.rekognition.search_faces_by_image(
+                            CollectionId=self.collectionId,
+                            Image={'Bytes': image_binary}
+                        )
+
+                if len(response['FaceMatches']) > 0:
+                    primary = True
+                    face_user = value[1]
+                        # x_face = (x1 + x2) / 2.0
+                        # y_face = (y1 + y2) / 2.0
+                    print('=====FACE MATCH=====')
+                        # plt.imshow(image)
+                        # plt.text(x_ff, y_ff, 'PRIMARY USER')
+                        # plt.axis('off')
+                        # mngr = plt.get_current_fig_manager()
+                        # mngr.window.wm_geometry('+380+310')
+                        # plt.pause(2)
+                        # plt.ioff
+                        # plt.clf()
+                        # plt.close()
+
+                        # points = ((x1, y1), (x2, y1), (x2, y2), (x1, y2), (x1, y1))
+                        # draw = ImageDraw.Draw(image)
+                        # draw.line(points, fill='#00d400', width=2)
+                        # draw.text((x_face, y_face), response['FaceMatches'][0]['Face']['ExternalImageId'], fill=(255, 255, 0))
+                #image.show()
+            except:
+                pass
+
+        return primary, face_user
 
     def __init__ (self):
         self.rekognition = boto3.client('rekognition', region_name='us-east-2')
@@ -124,7 +108,6 @@ def __init__ (self):
         # rekognition.create_collection(CollectionId=collectionId)
         # self.path of the training pics library of the primary user
         self.path_train = '/home/miro/jodie/MiRo/lib/fr_lib/train'
-        self.path_test = './user_pic.png'
 
 
 
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diff --git a/mdk/bin/shared/pca/pca.py b/mdk/bin/shared/pca/pca.py
new file mode 100644
index 0000000..885bfd2
--- /dev/null
+++ b/mdk/bin/shared/pca/pca.py
@@ -0,0 +1,196 @@
+#!/usr/bin/python
+# This is a MIRO ROS client for Python.
+
+import rospy
+# http://docs.ros.org/api/geometry_msgs/html/msg/TwistStamped.html
+from geometry_msgs.msg import TwistStamped
+
+import math
+import numpy as np
+import time
+import sys
+import os
+
+import cv2
+from cv_bridge import CvBridge, CvBridgeError
+from sensor_msgs.msg import CompressedImage
+import matplotlib.pyplot as plt
+import numpy.matlib
+
+# The miro2 Python module provides constants and tools for working with MiRo from Python.
+# with PYTHONPATH=~/mdk/share/python:$PYTHONPATH
+import miro2 as miro
+
+
+################################################################
+
+def error(msg):
+    print(msg)
+    sys.exit(0)
+
+
+################################################################
+
+class controller:
+    def callback_caml(self, ros_image):
+        # ignore until active
+        if not self.active:
+            return
+
+        self.image_converter = CvBridge()
+        # convert compressed ROS image to raw CV image
+
+        # image = self.image_converter.compressed_imgmsg_to_cv2(ros_image, "bgr8")
+        # if self.i < 20:
+        #     cv2.imwrite(str(self.i) + '.jpg', image)
+        #     time.sleep(2)
+
+        self.i += 1
+
+
+    def loop(self):
+        pass
+        # loop
+        while self.active and not rospy.core.is_shutdown():
+            if self.i == 20:
+                print('i = 20')
+                for i in range(20):
+                    print('processing' + str(i))
+                    image = self.getImage(str(i)+'.jpg')
+                    self.process(image)
+
+                plt.show()
+
+
+            # if self.i == 1:
+            #     print('is 1 ')
+            #     self.reader()
+            #     plt.show()
+
+
+
+
+
+
+
+
+
+        # cv2.destroyAllWindows()
+
+    def getImage(self,name):
+        img = cv2.imread(name)
+        res = cv2.resize(img, dsize = (self.s,self.s), interpolation=cv2.INTER_CUBIC)
+        res = np.mean(res,2)
+
+
+        return res
+
+
+    def process(self,res):
+
+        self.X[self.counter, :] = res.flatten()
+        # repeat this n times
+        # Apply PCA
+        h, w = self.X.shape
+        mu = np.reshape(np.mean(self.X, 1), (h, 1))
+        # Substract mean
+        self.X = self.X - np.matlib.repmat(mu, 1, w)
+        np.savetxt('test.out', self.X, delimiter=',')
+
+        # Covariance matrix
+        C = np.dot(self.X.T, self.X)
+        # Eigendecpmposition
+        d, v = np.linalg.eig(C)
+        # This the projection matrix
+        v = v[:, 0:2]
+        # Compute the projection
+        z = np.dot(v.T, res.flatten())
+        plt.plot(z[0], z[1], 'r*')
+        self.counter += 1
+
+
+
+    def reader(self):
+        print('a')
+        self.X = np.loadtxt('test.out', delimiter=',')
+        print('b')
+
+
+        # Covariance matrix
+        C = np.dot(self.X.T, self.X)
+        print(self.X)
+        print('c')
+        # Eigendecpmposition
+        d, v = np.linalg.eig(C)
+        print('d')
+        # This the projection matrix
+        v = v[:, 0:2]
+        # Compute the projection
+        print('e')
+        for i in self.X:
+            print('in')
+            z = np.dot(v.T, i)
+            plt.plot(z[0], z[1], 'r*')
+
+
+    def __init__(self, args):
+        rospy.init_node("client", anonymous=True)
+
+        self.n = 20
+        self.s = 64
+        self.X = np.zeros((self.n,self.s*self.s))
+
+       # sim
+        self.t = time.time()
+        self.i = 0
+        self.counter = 0
+
+
+        # state
+        self.t_now = 0.0
+        self.active = False
+
+        # handle args
+        for arg in args:
+            f = arg.find('=')
+            if f == -1:
+                key = arg
+                val = ""
+            else:
+                key = arg[:f]
+                val = arg[f + 1:]
+            if key == "pass":
+                pass
+            else:
+                error("argument not recognised \"" + arg + "\"")
+
+        # robot name
+        topic_base_name = "/" + os.getenv("MIRO_ROBOT_NAME")
+
+        # publish
+        # topic = topic_base_name + "/control/cmd_vel"
+        # print("publish", topic)
+        # self.pub_cmd_vel = rospy.Publisher(topic, TwistStamped, queue_size=0)
+
+        # subscribe
+        # sensors/caml, Frames from the left eye camera (sample rate is variable, see control/command).
+        topicCamLeft = topic_base_name + "/sensors/caml/compressed"
+        print("subscribe", topicCamLeft)
+        self.sub_caml = rospy.Subscriber(topicCamLeft, CompressedImage, self.callback_caml, queue_size=1,
+                                         tcp_nodelay=True)
+
+        # wait for connect
+        print
+        "wait for connect..."
+        time.sleep(1)
+
+        # set to active
+        self.active = True
+
+
+if __name__ == "__main__":
+    main = controller(sys.argv[1:])
+    main.loop()
+
+
+
diff --git a/mdk/bin/shared/pca/test.out b/mdk/bin/shared/pca/test.out
new file mode 100644
index 0000000..03f832f
--- /dev/null
+++ b/mdk/bin/shared/pca/test.out
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diff --git a/mdk/share/python/miro2/core/client_demo.py b/mdk/share/python/miro2/core/client_demo.py
index b0a1e49..ca9c7eb 100755
--- a/mdk/share/python/miro2/core/client_demo.py
+++ b/mdk/share/python/miro2/core/client_demo.py
@@ -248,7 +248,7 @@ def __init__(self, client_type):
 		self.sub = []
 
 		# select client type
-		if self.client_type == "main":
+		if self.client_type tick== "main":
 
 			# publish priority
 			self.pub_pri = [
diff --git a/mdk/share/python/miro2/utils/.kc.py.swp b/mdk/share/python/miro2/utils/.kc.py.swp
deleted file mode 100644
index 7893aa63460578cef83d33840b5abacff366187d..0000000000000000000000000000000000000000
GIT binary patch
literal 0
HcmV?d00001

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From 2c543a608d85b06d527d5aeb4916d332e50aad21 Mon Sep 17 00:00:00 2001
From: jodie <liws18uk@yeah.net>
Date: Mon, 2 Sep 2019 20:56:56 +0100
Subject: [PATCH 21/32] add node fr

---
 Client_weishi/detect_primary_user.py          |  2 +-
 mdk/share/python/miro2/core/client_demo.py    | 18 ++++-
 mdk/share/python/miro2/core/node.py           |  2 +-
 .../python/miro2/core/node_detect_face.py     | 10 ++-
 .../miro2/core/node_face_recognition.py       | 73 +++++++++++++++++++
 mdk/share/python/miro2/core/pars.py           |  1 +
 6 files changed, 100 insertions(+), 6 deletions(-)
 create mode 100644 mdk/share/python/miro2/core/node_face_recognition.py

diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index b8ecdc1..4050cf0 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -3,7 +3,7 @@
 import io
 import os
 import numpy as np
-from PIL import Image, ImageDraw, ImageFont
+from PIL import Image
 import matplotlib.pyplot as plt
 
 # face detection
diff --git a/mdk/share/python/miro2/core/client_demo.py b/mdk/share/python/miro2/core/client_demo.py
index ca9c7eb..8c100ab 100755
--- a/mdk/share/python/miro2/core/client_demo.py
+++ b/mdk/share/python/miro2/core/client_demo.py
@@ -57,6 +57,7 @@
 from node_detect_face import *
 from node_detect_audio import *
 from node_spatial import *
+from node_face_recognition import *
 
 
 
@@ -140,7 +141,9 @@ def __init__(self, pars):
 
 		# detected objects
 		self.detect_ball = [None, None]
-		self.detect_face = [None, None]
+		# detect_face [faces_coordinate, image]
+		self.detect_face = [[], []]
+		self.primary_user = False
 
 		# internal
 		self.reconfigure_cameras = False
@@ -183,12 +186,21 @@ def instantiate(self, sys):
 			self.decode = NodeDecode(sys)
 			self.detect_motion = NodeDetectMotion(sys)
 			self.detect_face = NodeDetectFace(sys)
+			self.face_recognition = NodeFaceRecognition(sys)
 			self.detect_ball = NodeDetectBall(sys)
 
 		# instantiate
 		if self.client_type == "mics":
 			self.detect_audio = NodeDetectAudio(sys)
 
+
+		# # instantiate
+		# if self.client_type == "recognition":
+		# 	self.decode = NodeDecode(sys)
+		# 	self.detect_face = NodeDetectFace(sys)
+
+
+
 	def tick(self):
 
 		# tick
@@ -248,7 +260,7 @@ def __init__(self, client_type):
 		self.sub = []
 
 		# select client type
-		if self.client_type tick== "main":
+		if self.client_type == "main":
 
 			# publish priority
 			self.pub_pri = [
@@ -448,7 +460,7 @@ def callback_sensors_package(self, msg):
 
 		# publish motor output
 		if self.use_external_kc:
-			for push in self.output.pushes:
+
 				msg = self.pub_push.msg
 				msg.pushpos = geometry_msgs.msg.Vector3(push.pos[0], push.pos[1], push.pos[2])
 				msg.pushvec = geometry_msgs.msg.Vector3(push.vec[0], push.vec[1], push.vec[2])
diff --git a/mdk/share/python/miro2/core/node.py b/mdk/share/python/miro2/core/node.py
index 55806a9..59404bb 100644
--- a/mdk/share/python/miro2/core/node.py
+++ b/mdk/share/python/miro2/core/node.py
@@ -38,7 +38,7 @@
 import miro2 as miro
 
 
-
+# node template
 class Node(object):
 
 	def __init__(self, sys, node_name):
diff --git a/mdk/share/python/miro2/core/node_detect_face.py b/mdk/share/python/miro2/core/node_detect_face.py
index 7c158a8..8d24481 100644
--- a/mdk/share/python/miro2/core/node_detect_face.py
+++ b/mdk/share/python/miro2/core/node_detect_face.py
@@ -72,6 +72,8 @@ def tick_camera(self, stream_index):
 
 		# get image (grayscale)
 		img = self.state.frame_gry[stream_index]
+		img_raw = self.state.frame_raw[stream_index] =
+
 
 		# load test image
 		if self.pars.flags.DEV_DETECT_FACE and stream_index == 0 and (self.ticks[stream_index] & 30) < 1:
@@ -81,6 +83,7 @@ def tick_camera(self, stream_index):
 
 		# search image with each classifier
 		faces = []
+		roi_color = None
 		for cascade in self.cascades:
 			f = cascade.detectMultiScale3(img, 1.05, 3, 0, (20, 20), outputRejectLevels=True)
 			rects = f[0]
@@ -96,12 +99,17 @@ def tick_camera(self, stream_index):
 					face = np.concatenate((rect, conf))
 					faces.append(face)
 
+					for face in faces:
+						x, y, w, h, conf = face
+						roi_color = img_raw[x:x+w, y:y+h]
+
+
 		# merge duplicates
 		# let's not do this for now, I'm not sure why it's needed yet
 		#faces = self.merge_duplicates(faces)
 
 		# store
-		self.state.detect_face[stream_index] = faces
+		self.state.detect_face[stream_index] = [faces, roi_color]
 
 		# tick
 		self.ticks[stream_index] += 1
diff --git a/mdk/share/python/miro2/core/node_face_recognition.py b/mdk/share/python/miro2/core/node_face_recognition.py
new file mode 100644
index 0000000..27c8e27
--- /dev/null
+++ b/mdk/share/python/miro2/core/node_face_recognition.py
@@ -0,0 +1,73 @@
+import node
+
+import boto3
+
+import io
+
+import os
+
+import cv2
+
+import numpy as np
+
+from PIL import Image
+
+
+
+class NodeFaceRecognition(node.Node):
+
+    def __init__(self, sys):
+        node.Node.__init__(self, sys, "face_recognition")
+
+        self.rekognition = boto3.client('rekognition', region_name='us-east-2')
+        self.collectionId = 'primary_user'
+        try:
+            # create a collection
+            self.rekognition.create_collection(CollectionId=self.collectionId)
+        except:
+            pass
+
+        # add training faces into the collection
+        self.path_train = '/home/miro/jodie/MiRo/lib/fr_lib/train'
+        username = 'USER'
+        for r, d, f in os.walk(self.path_train):
+            for file in f:
+                if file != '.DS_Store':
+                    sourceFile = os.path.join(r, file)
+                    imageSource = open(sourceFile, 'rb')
+                    # adding faces to a Collection
+                    self.rekognition.index_faces(
+                            Image={'Bytes': imageSource.read()},
+                            ExternalImageId=username,
+                            CollectionId=self.collectionId)
+
+    def tick_camera(self, stream_index):
+        # faces is the array of detected faces from node_detect_face
+        detect_faces = self.state.detect_face[stream_index]
+
+        for d_face in detect_faces:
+            face = d_face[1]
+
+            array = cv2.cvtColor(np.array(face), cv2.COLOR_RGB2BGR)
+            image = Image.fromarray(array)
+
+            # image convert to binary
+            stream = io.BytesIO()
+            image.save(stream, format="JPEG")
+            image_binary = stream.getvalue()
+
+            # use image search faces in the Collection
+            try:
+                response = self.rekognition.search_faces_by_image(
+                    CollectionId=self.collectionId,
+                    Image={'Bytes': image_binary}
+                )
+
+                if len(response['FaceMatches']) > 0:
+                    self.state.primary_user = True
+                    # face = d_face[0]
+                    print('=====FACE MATCH=====')
+            except:
+                pass
+
+        # return  face
\ No newline at end of file
diff --git a/mdk/share/python/miro2/core/pars.py b/mdk/share/python/miro2/core/pars.py
index d3d73e8..95c8644 100644
--- a/mdk/share/python/miro2/core/pars.py
+++ b/mdk/share/python/miro2/core/pars.py
@@ -452,6 +452,7 @@ def __init__( self ):
 		self.DEV_DEBUG_ACTION_PARAMS	= 1
 		self.DEV_DEBUG_ORIENT_START		= 0
 		self.DEV_SEND_DEBUG_TOPICS		= 0
+		self.DEV_PRIMARY_USER           = 0
 
 		# developer flags accessible from MIROapp (for now)
 		self.DEV_DEBUG_SONAR			= 0

From e7d579037b8de0a801bfa661febeadc59c1fd27a Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Thu, 5 Sep 2019 20:03:39 +0100
Subject: [PATCH 22/32] test

---
 Client_weishi/client.py                       | 139 ++++++++++--------
 Client_weishi/detect_primary_user.py          |   2 +-
 mdk/share/python/miro2/core/client_demo.py    |  20 ++-
 mdk/share/python/miro2/core/node_decode.py    |   1 +
 .../python/miro2/core/node_detect_face.py     |  16 ++
 5 files changed, 110 insertions(+), 68 deletions(-)

diff --git a/Client_weishi/client.py b/Client_weishi/client.py
index f4dda25..74b2d74 100644
--- a/Client_weishi/client.py
+++ b/Client_weishi/client.py
@@ -77,20 +77,23 @@ def track(self):
             # Move head up
             # print('hf > epsilon. move head up')
             # a = self.kin_joints.position[lift]
-            self.kin_joints.position[lift] = self.kin_joints.position[lift] + hf*miro.constants.LIFT_RAD_MIN/self.image_height
+            self.kin_joints.position[lift] = self.kin_joints.position[lift] + 1.5*hf*miro.constants.LIFT_RAD_MIN/self.image_height
             # print('after moving, degree: ', (self.kin_joints.position[lift]-a)/0.0174532)
+            print(self.kin_joints.position[lift])
+            # if self.kin_joints.position[lift] < miro.constants.LIFT_RAD_MIN:
+            #     self.kin_joints.position[pitch] = self.kin_joints.position[pitch] - 2*hf*miro.constants.PITCH_RAD_MIN/self.image_height
 
         elif hf > epsilon and self.kin_joints.position[lift] < miro.constants.LIFT_RAD_MAX:
             # Move head down
-            print('hf < epsilon. move head down')
-            a = self.kin_joints.position[lift]
-            self.kin_joints.position[lift] = self.kin_joints.position[lift] + hf*miro.constants.LIFT_RAD_MAX/self.image_height
-            print('after moving, degree: ', self.kin_joints.position[lift]-a)
+            # print('hf < epsilon. move head down')
+            # a = self.kin_joints.position[lift]
+            self.kin_joints.position[lift] = self.kin_joints.position[lift] + 1.5*hf*miro.constants.LIFT_RAD_MAX/self.image_height
+            # print('after moving, degree: ', self.kin_joints.position[lift]-a)
 
         self.pub_kin.publish(self.kin_joints)
 
-        end_track = time.time()
-        print('******************time of tracking: ', end_track - st_track)
+        # end_track = time.time()
+        # print('******************time of tracking: ', end_track - st_track)
 
         time.sleep(0.3)
 
@@ -111,11 +114,11 @@ def do_detection(self):
     def do_recognition(self):
 
         # PRIMARY USER RECOGNITION, GET X,Y OF THE PRIMARY USER
-        st = time.time()
+        # st = time.time()
         # self.faces is the dictionary of faces include roi & coordinate of face center
         self.primary_detected, self.face_user = self.det_pri_user.face_recognition(self.faces)
-        et = time.time()
-        print('******************time of recognition: ', et - st)
+        # et = time.time()
+        # print('******************time of recognition: ', et - st)
 
         # x = self.face_user[0]
         # y = self.face_user[1]
@@ -141,8 +144,6 @@ def get_face_distance(self, wf, hf):
         d = 0.0
         area_face = wf * hf
         area_image = 640 * 360
-        # print ('&&&&&  face width  &&&&&    ', wf)
-        # print ('&&&&&  face height &&&&&    ', hf)
         d = (area_face * 1.0) / area_image
 
         return d
@@ -159,53 +160,44 @@ def move(self, wheel_speed):
         self.pub_cmd_vel.publish(self.velocity)
 
     def miro_approach(self):
+        print(self.i, 'th approach')
+        self.i += 1
         tilt, lift, yaw, pitch = range(4)
-        if self.kin_joints.position[yaw] < -(20*0.0174532):
+        if self.kin_joints.position[yaw] < -(5*0.0174532):
             # move right
-            print('@@@@@@', self.kin_joints.position[yaw]/0.0174532)
-            print('@@@@@@move right')
-            self.run_sec('R')
-        elif self.kin_joints.position[yaw] > (20*0.0174532):
+            # print('---', self.kin_joints.position[yaw]/0.0174532)
+            print('---move right')
+            # self.run_sec('R')
+            wheel_speed = [0.3, 0.0]
+            self.move(wheel_speed)
+        elif self.kin_joints.position[yaw] > (5*0.0174532):
             # move left
-            print('@@@@@@', self.kin_joints.position[yaw]/0.0174532)
-            print('@@@@@@move left')
-            self.run_sec('L')
-        else:
-            # move forward
-            print('@@@@@@move forward')
-            self.run_sec('U')
-        time.sleep(2)
-
-
-        print('@@@@@@after running for 0.2s')
-
-        # wheel_speed = [1.0, 1.0]
-        #
-        # self.do_detection()
-        # if self.faces != {}:
-        #     self.do_recognition()
-        #     if self.primary_detected == True:
-        #         # get close to user
-        #         d = self.get_face_distance(self.face_user[2], self.face_user[3])
-        #         while d > 0.05:
-        #             print('loop distance: ', d)
-        #             self.move(wheel_speed)
-        #             self.do_detection()
-        #             if self.faces != {}:
-        #                 self.do_recognition()
-        #                 if self.primary_detected == True:
-        #                     # get close to user
-        #                     d = self.get_face_distance(self.face_user[2], self.face_user[3])
-        # time.sleep(1)
+            # print('---', self.kin_joints.position[yaw]/0.0174532)
+            print('---move left')
+            # self.run_sec('L')
+            wheel_speed = [0.0, 0.3]
+            self.move(wheel_speed)
+
+        # move forward
+        # print('---', self.kin_joints.position[yaw] / 0.0174532)
+        print('---move forward')
+        # self.run_sec('U')
+        wheel_speed = [0.4, 0.4]
+        self.move(wheel_speed)
+        time.sleep(0.3)
+
+
+        print('---after running for 0.2s')
+
 
     # miro go straight for 0.1s
     def run_sec(self, direction):
 
-        if direction == 'R':
-            wheel_speed = [0.2, 0.0]
-        elif direction == 'L':
-            wheel_speed = [0.0, 0.2]
-        elif direction == 'U':
+        # if direction == 'R':
+        #     wheel_speed = [0.2, 0.0]
+        # elif direction == 'L':
+        #     wheel_speed = [0.0, 0.2]
+        if direction == 'U':
             wheel_speed = [0.2, 0.2]
 
         start = datetime.datetime.now()
@@ -235,16 +227,41 @@ def loop(self):
             if self.faces != {}:
                 self.do_recognition()
                 if self.primary_detected == True:
+                    # print('\n')
+                    # print('\n')
+                    # print('detected the primary user')
                     self.track()
-                    # get close to user
-                    distance = self.get_face_distance(self.face_user[2], self.face_user[3])
-                    print('&&&&&  distance  &&&&&    ', distance)
-                    if distance < 0.02:
-                        self.miro_approach()
+                    # # get close to user
+                    # distance = self.get_face_distance(self.face_user[2], self.face_user[3])
+                    # print('-----  distance  ----- ', distance)
+                    # if distance < 0.05:
+                    #     self.miro_approach()
 
-            # track any face
-            # if self.x_primary != None:
-            #     self.track(self.x_primary, self.y_primary, 640, 360)
+            else:
+                # print('No user, stop!!!!!')
+                # set speed to zero
+                self.velocity.twist.linear.x = 0.0
+                self.velocity.twist.angular.z = 0.0
+                self.pub_cmd_vel.publish(self.velocity)
+
+            # # track any user
+            # if self.faces != {}:
+            #     # self.do_recognition()
+            #     time.sleep(0.8)
+            #     self.face_user = self.faces[0][1]
+            #     self.x_primary = self.face_user[0] + self.face_user[2] / 2
+            #     self.y_primary = self.face_user[1] + self.face_user[3] / 2
+            #     self.track()
+            #     # get close to user
+            #     distance = self.get_face_distance(self.face_user[2], self.face_user[3])
+            #     print('&&&&&  distance  &&&&&    ', distance)
+            #     if distance < 0.05:
+            #         self.miro_approach()
+            #
+            #     else:
+            #         # set speed to zero
+            #         wheel_speed0 = [0.0, 0.0]
+            #         self.move(wheel_speed0)
 
             # Show the frames and ROI
             if self.detected_faces != None:
@@ -292,6 +309,8 @@ def __init__(self, args):
 
         self.velocity = TwistStamped()
 
+        self. i = 0
+
         # the object of detect_primary_user
         self.det_pri_user = detect_primary_user()
         # create the diff images of user collection
diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index b8ecdc1..3dfb871 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -80,7 +80,7 @@ def face_recognition(self, dic_faces):
                     face_user = value[1]
                         # x_face = (x1 + x2) / 2.0
                         # y_face = (y1 + y2) / 2.0
-                    print('=====FACE MATCH=====')
+                    # print('=====FACE MATCH=====')
                         # plt.imshow(image)
                         # plt.text(x_ff, y_ff, 'PRIMARY USER')
                         # plt.axis('off')
diff --git a/mdk/share/python/miro2/core/client_demo.py b/mdk/share/python/miro2/core/client_demo.py
index ca9c7eb..0f62f75 100755
--- a/mdk/share/python/miro2/core/client_demo.py
+++ b/mdk/share/python/miro2/core/client_demo.py
@@ -248,7 +248,7 @@ def __init__(self, client_type):
 		self.sub = []
 
 		# select client type
-		if self.client_type tick== "main":
+		if self.client_type == "main":
 
 			# publish priority
 			self.pub_pri = [
@@ -303,12 +303,12 @@ def __init__(self, client_type):
 
 			# publish detection summary (debug)
 			self.pub_sum = self.publish('core/sum' + self.camera_sub, sensor_msgs.msg.Image)
-
-			# publish ball detector state (debug)
+                                                                                 
+			# publish ball detector state (debug)                    
 			self.pub_bal = self.publish('core/bal' + self.camera_sub, sensor_msgs.msg.Image)
-
-		# select client type
-		if self.client_type == "mics":
+                                                                                 
+		# select client type                                             
+		if self.client_type == "mics":                                   
 
 			# publish
 			self.pub_mics = self.publish('core/audio_event', std_msgs.msg.Float32MultiArray)
@@ -552,6 +552,7 @@ def callback_movr(self, msg):
 		self.callback_mov(1, msg)
 
 	def callback_cam(self, msg):
+		#print('callback camera')
 
 		stream_index = self.stream_index
 
@@ -561,15 +562,19 @@ def callback_cam(self, msg):
 		if self.active_counter == 0:
 			return
 
-		self.active_counter -= 1
+		#self.active_counter -= 1
+
 		if self.active_counter == 0:
 			print "going inactive..."
 			return
 
+
 		if not self.timing0 is None:
 			self.timing[1].append(time.time() - self.timing0)
 
+
 		# tick camera
+		# get img and store
 		if self.nodes.decode.tick_camera(stream_index, msg):
 
 			# tick_camera returns true to indicate the frame
@@ -587,6 +592,7 @@ def callback_cam(self, msg):
 		# tick
 		self.nodes.detect_motion.tick_camera(stream_index)
 		self.nodes.detect_face.tick_camera(stream_index)
+
 		self.nodes.detect_ball.tick_camera(stream_index)
 
 		# publish result
diff --git a/mdk/share/python/miro2/core/node_decode.py b/mdk/share/python/miro2/core/node_decode.py
index 0241d14..a81d36b 100644
--- a/mdk/share/python/miro2/core/node_decode.py
+++ b/mdk/share/python/miro2/core/node_decode.py
@@ -77,6 +77,7 @@ def tick_camera(self, stream_index, msg):
 			sc = float(des_image_height) / img.shape[0]
 			img = cv2.resize(img, dsize=(0, 0), fx=sc, fy=sc)
 
+
 		# store raw
 		self.state.frame_raw[stream_index] = img
 
diff --git a/mdk/share/python/miro2/core/node_detect_face.py b/mdk/share/python/miro2/core/node_detect_face.py
index 7c158a8..ea08930 100644
--- a/mdk/share/python/miro2/core/node_detect_face.py
+++ b/mdk/share/python/miro2/core/node_detect_face.py
@@ -40,6 +40,11 @@
 import cv2
 from cv_bridge import CvBridge
 
+# for testing
+from PIL import Image
+from PIL import ImageDraw
+import matplotlib.pyplot as plt
+
 
 
 class NodeDetectFace(node.Node):
@@ -72,6 +77,10 @@ def tick_camera(self, stream_index):
 
 		# get image (grayscale)
 		img = self.state.frame_gry[stream_index]
+		# img_roi = self.state.frame_raw[stream_index]
+		# #-----------------------------
+		# cv2.imshow('face', img_roi)
+		# cv2.waitKey(1)
 
 		# load test image
 		if self.pars.flags.DEV_DETECT_FACE and stream_index == 0 and (self.ticks[stream_index] & 30) < 1:
@@ -81,6 +90,7 @@ def tick_camera(self, stream_index):
 
 		# search image with each classifier
 		faces = []
+		# roi_color = []
 		for cascade in self.cascades:
 			f = cascade.detectMultiScale3(img, 1.05, 3, 0, (20, 20), outputRejectLevels=True)
 			rects = f[0]
@@ -95,6 +105,10 @@ def tick_camera(self, stream_index):
 					#print "detected face", stream_index, conf, rect
 					face = np.concatenate((rect, conf))
 					faces.append(face)
+					# x, y, w, h, conf = face
+					# roi = img_roi[x:x+w, y:y+h]
+					# roi_color.append(roi)
+
 
 		# merge duplicates
 		# let's not do this for now, I'm not sure why it's needed yet
@@ -105,6 +119,8 @@ def tick_camera(self, stream_index):
 
 		# tick
 		self.ticks[stream_index] += 1
+		# -------------------------
+		cv2.destroyAllWindows()
 
 	def merge_duplicates(self, faces):
 

From 98342c99f7a7b92e2f8842106ecfd09735244cae Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Fri, 6 Sep 2019 18:33:50 +0100
Subject: [PATCH 23/32] test face detected

---
 mdk/share/python/miro2/core/client_demo.py    |  8 ++---
 mdk/share/python/miro2/core/node_decode.py    |  7 +++--
 .../python/miro2/core/node_detect_face.py     | 31 ++++++-------------
 .../miro2/core/node_face_recognition.py       | 20 ++++--------
 mdk/share/python/miro2/core/pars.py           |  2 +-
 5 files changed, 25 insertions(+), 43 deletions(-)

diff --git a/mdk/share/python/miro2/core/client_demo.py b/mdk/share/python/miro2/core/client_demo.py
index 35ac2c8..c524359 100755
--- a/mdk/share/python/miro2/core/client_demo.py
+++ b/mdk/share/python/miro2/core/client_demo.py
@@ -142,7 +142,7 @@ def __init__(self, pars):
 		# detected objects
 		self.detect_ball = [None, None]
 		# detect_face [faces_coordinate, image]
-		self.detect_face = [[], []]
+		self.detect_face = [None, None]
 		self.primary_user = False
 
 		# internal
@@ -186,7 +186,7 @@ def instantiate(self, sys):
 			self.decode = NodeDecode(sys)
 			self.detect_motion = NodeDetectMotion(sys)
 			self.detect_face = NodeDetectFace(sys)
-			self.face_recognition = NodeFaceRecognition(sys)
+		#	self.face_recognition = NodeFaceRecognition(sys)
 			self.detect_ball = NodeDetectBall(sys)
 
 		# instantiate
@@ -254,7 +254,7 @@ def __init__(self, client_type):
 
 		# monitor use of time (set timing0 to "None" to disable timing)
 		self.timing = [[], [], []]
-		self.timing0 = None # time.time()
+		self.timing0 = None  # time.time()
 
 		# ROS interfaces
 		self.sub = []
@@ -604,7 +604,7 @@ def callback_cam(self, msg):
 		# tick
 		self.nodes.detect_motion.tick_camera(stream_index)
 		self.nodes.detect_face.tick_camera(stream_index)
-
+		# self.nodes.face_recognition.tick_camera(stream_index)
 		self.nodes.detect_ball.tick_camera(stream_index)
 
 		# publish result
diff --git a/mdk/share/python/miro2/core/node_decode.py b/mdk/share/python/miro2/core/node_decode.py
index a81d36b..40852b6 100644
--- a/mdk/share/python/miro2/core/node_decode.py
+++ b/mdk/share/python/miro2/core/node_decode.py
@@ -67,9 +67,10 @@ def tick_camera(self, stream_index, msg):
 
 		# check image size - we are now only accepting the correct
 		# image size, and we'll raise a flag to correct it if not
-		if img.shape != (176, 320, 3):
-			print "image wrong size"
-			return True
+		# if img.shape != (176, 320, 3):
+		# 	print "image wrong size"
+		# 	print(img.shape)
+		# 	return True
 
 		# resize image to the size we process at in the demo
 		des_image_height = self.pars.decode.image_height
diff --git a/mdk/share/python/miro2/core/node_detect_face.py b/mdk/share/python/miro2/core/node_detect_face.py
index cc83e14..2e78419 100644
--- a/mdk/share/python/miro2/core/node_detect_face.py
+++ b/mdk/share/python/miro2/core/node_detect_face.py
@@ -77,15 +77,11 @@ def tick_camera(self, stream_index):
 
 		# get image (grayscale)
 		img = self.state.frame_gry[stream_index]
-<<<<<<< HEAD
+
 		# img_roi = self.state.frame_raw[stream_index]
-		# #-----------------------------
+		#-----------------------------
 		# cv2.imshow('face', img_roi)
 		# cv2.waitKey(1)
-=======
-		img_raw = self.state.frame_raw[stream_index] =
-
->>>>>>> 2c543a608d85b06d527d5aeb4916d332e50aad21
 
 		# load test image
 		if self.pars.flags.DEV_DETECT_FACE and stream_index == 0 and (self.ticks[stream_index] & 30) < 1:
@@ -95,11 +91,7 @@ def tick_camera(self, stream_index):
 
 		# search image with each classifier
 		faces = []
-<<<<<<< HEAD
-		# roi_color = []
-=======
-		roi_color = None
->>>>>>> 2c543a608d85b06d527d5aeb4916d332e50aad21
+
 		for cascade in self.cascades:
 			f = cascade.detectMultiScale3(img, 1.05, 3, 0, (20, 20), outputRejectLevels=True)
 			rects = f[0]
@@ -114,22 +106,19 @@ def tick_camera(self, stream_index):
 					#print "detected face", stream_index, conf, rect
 					face = np.concatenate((rect, conf))
 					faces.append(face)
-					# x, y, w, h, conf = face
-					# roi = img_roi[x:x+w, y:y+h]
-					# roi_color.append(roi)
-
-
-					for face in faces:
-						x, y, w, h, conf = face
-						roi_color = img_raw[x:x+w, y:y+h]
-
 
 		# merge duplicates
 		# let's not do this for now, I'm not sure why it's needed yet
 		#faces = self.merge_duplicates(faces)
 
 		# store
-		self.state.detect_face[stream_index] = [faces, roi_color]
+		self.state.detect_face[stream_index] = faces
+
+		# report face detected
+		if faces != []:
+			print 'detect face', faces
+			cv2.imshow('detected_face', faces)
+			cv2.waitKey(1)
 
 		# tick
 		self.ticks[stream_index] += 1
diff --git a/mdk/share/python/miro2/core/node_face_recognition.py b/mdk/share/python/miro2/core/node_face_recognition.py
index 27c8e27..843e774 100644
--- a/mdk/share/python/miro2/core/node_face_recognition.py
+++ b/mdk/share/python/miro2/core/node_face_recognition.py
@@ -1,19 +1,11 @@
 import node
-
 import boto3
-
 import io
-
 import os
-
 import cv2
-
 import numpy as np
-
 from PIL import Image
 
-
-
 class NodeFaceRecognition(node.Node):
 
     def __init__(self, sys):
@@ -43,10 +35,12 @@ def __init__(self, sys):
 
     def tick_camera(self, stream_index):
         # faces is the array of detected faces from node_detect_face
-        detect_faces = self.state.detect_face[stream_index]
+        faces = self.state.detect_face[stream_index]
+        img = self.state.frame_raw[stream_index]
 
-        for d_face in detect_faces:
-            face = d_face[1]
+        for face in faces:
+            (x, y, w, h, conf) = face
+            face = img[x:x+w, y:y+h]
 
             array = cv2.cvtColor(np.array(face), cv2.COLOR_RGB2BGR)
             image = Image.fromarray(array)
@@ -64,10 +58,8 @@ def tick_camera(self, stream_index):
                 )
 
                 if len(response['FaceMatches']) > 0:
+                    # store
                     self.state.primary_user = True
-                    # face = d_face[0]
                     print('=====FACE MATCH=====')
             except:
                 pass
-
-        # return  face
\ No newline at end of file
diff --git a/mdk/share/python/miro2/core/pars.py b/mdk/share/python/miro2/core/pars.py
index 95c8644..76d9308 100644
--- a/mdk/share/python/miro2/core/pars.py
+++ b/mdk/share/python/miro2/core/pars.py
@@ -185,7 +185,7 @@ class Decode(object):
 	def __init__(self):
 
 		# image height at which we process within demo
-		self.image_height = 100 # 90, 100, 120, 150
+		self.image_height = 100  # 90, 100, 120, 150
 
 	def finalize(self, pars):
 

From 5bb55a0f1bd190b712be9c518d65a6a9a5d19cc4 Mon Sep 17 00:00:00 2001
From: YaKuRei <827752559@qq.com>
Date: Mon, 16 Sep 2019 13:26:58 +0100
Subject: [PATCH 24/32] update test search

---
 .../python/miro2/core/action/action_search.py | 155 ++++++++++++++++++
 1 file changed, 155 insertions(+)
 create mode 100644 mdk/share/python/miro2/core/action/action_search.py

diff --git a/mdk/share/python/miro2/core/action/action_search.py b/mdk/share/python/miro2/core/action/action_search.py
new file mode 100644
index 0000000..e76d5f4
--- /dev/null
+++ b/mdk/share/python/miro2/core/action/action_search.py
@@ -0,0 +1,155 @@
+#	@section COPYRIGHT
+#	Copyright (C) 2019 Consequential Robotics Ltd
+#
+#	@section AUTHOR
+#	Consequential Robotics http://consequentialrobotics.com
+#
+#	@section LICENSE
+#	For a full copy of the license agreement, and a complete
+#	definition of "The Software", see LICENSE in the MDK root
+#	directory.
+#
+#	Subject to the terms of this Agreement, Consequential
+#	Robotics grants to you a limited, non-exclusive, non-
+#	transferable license, without right to sub-license, to use
+#	"The Software" in accordance with this Agreement and any
+#	other written agreement with Consequential Robotics.
+#	Consequential Robotics does not transfer the title of "The
+#	Software" to you; the license granted to you is not a sale.
+#	This agreement is a binding legal agreement between
+#	Consequential Robotics and the purchasers or users of "The
+#	Software".
+#
+#	THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY
+#	KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
+#	WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
+#	PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS
+#	OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR
+#	OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR
+#	OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+#	SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+#
+#
+#	Action search
+#	action for MIRO to search master's face
+
+
+import numpy as np
+import tf
+import rospy
+import copy
+import miro2 as miro
+
+from action_types import ActionTemplate
+
+
+
+class ActionSearch(ActionTemplate):
+
+    def finalize(self):
+
+        # parameters
+        self.name = "search"
+        self.retreatable = True
+
+    def compute_priority(self):
+
+        # extract variables
+        valence = self.input.emotion.valence
+        arousal = self.input.emotion.arousal
+        height = self.input.priority_peak.height
+        size_norm = self.input.priority_peak.size_norm
+        fixation = self.input.fixation
+
+        # extract pars
+        base_priority = self.pars.action.approach_base_prio
+        size_gain = self.pars.action.approach_size_gain
+        arousal_gain = self.pars.action.approach_arousal_gain
+        valence_gain = self.pars.action.approach_valence_gain
+        fixation_gain = self.pars.action.approach_fixation_gain
+
+        # compute priority
+        tend_some = np.tanh(arousal_gain * (arousal - 0.5) + fixation_gain * (fixation - 0.5))
+        tend_appe = np.tanh(valence_gain * (valence - 0.5) - size_gain * (size_norm - 0.5))
+        priority = height * (base_priority + tend_some + tend_appe)
+
+        # modulate by cliff and sonar
+        priority *= self.input.conf_surf
+        priority *= self.input.conf_space
+
+        # modulate for dev
+        if self.pars.flags.DEV_ORIENT_ONLY:
+            priority = 0.0
+
+        # ok set the max priority, then we can only do search action and test it ~lucy
+        return self.pars.action.priority_uninterruptable  #priority
+
+    def event_start(self):
+
+        self.appetitive_response(self.pars.action.approach_appetitive_commitment)
+        self.debug_event_start()
+
+    def start(self):
+
+        # compute start point for fovea in WORLD
+        self.fovea_i_WORLD = self.kc.changeFrameAbs(miro.constants.LINK_HEAD, miro.constants.LINK_WORLD, self.fovea_HEAD)
+
+        # compute end point for fovea in WORLD
+        fovea_f_WORLD = self.kc.changeFrameAbs(
+                miro.constants.LINK_HEAD,
+                miro.constants.LINK_WORLD,
+                miro.utils.kc_interf.kc_view_to_HEAD(
+                    self.input.priority_peak.azim,
+                    self.input.priority_peak.elev,
+                    self.input.priority_peak.range
+                    )
+                )
+
+        # limit end point to be reachable
+        fovea_f_WORLD[2] = np.clip(fovea_f_WORLD[2],
+                            self.pars.geom.reachable_z_min,
+                            self.pars.geom.reachable_z_max
+                            )
+
+        # compute total movement fovea will make in world
+        self.dfovea_WORLD = fovea_f_WORLD - self.fovea_i_WORLD
+
+        # compute pattern time
+        total_dist = np.linalg.norm(self.dfovea_WORLD)
+        secs_ideal = total_dist * self.pars.action.approach_speed_spm
+        steps_ideal = int(secs_ideal * self.pars.timing.tick_hz)
+        steps_constrained = np.clip(steps_ideal,
+                    self.pars.action.approach_min_steps,
+                    self.pars.action.approach_max_steps
+                    )
+
+        # start pattern
+        self.clock.start(steps_constrained)
+
+        # debug
+        if self.debug:
+            print "fovea_i_WORLD", self.fovea_i_WORLD
+            print "fovea_f_WORLD", fovea_f_WORLD
+            print "pattern time", total_dist, secs_ideal, steps_ideal, steps_constrained
+
+    def service(self):
+
+        # read clock
+        x = self.clock.cosine_profile()
+        self.clock.advance(True)
+
+        # compute an interim target along a straight trajectory
+        fovea_x_WORLD = x * self.dfovea_WORLD + self.fovea_i_WORLD
+
+        # transform interim target into HEAD for actioning
+        fovea_x_HEAD = self.kc.changeFrameAbs(miro.constants.LINK_WORLD, miro.constants.LINK_HEAD, fovea_x_WORLD)
+
+        # apply push
+        self.apply_push_fovea(fovea_x_HEAD - self.fovea_HEAD)
+
+        # debug fovea movement through WORLD
+        #fovea_WORLD = self.kc.changeFrameAbs(miro.constants.LINK_HEAD, miro.constants.LINK_WORLD, self.fovea_HEAD)
+        #print "fovea_WORLD", fovea_WORLD, self.clock.toString()
+
+
+

From 9f7ffc497fbad4a91902a29a9a5f1931dd710910 Mon Sep 17 00:00:00 2001
From: YaKuRei <827752559@qq.com>
Date: Mon, 16 Sep 2019 13:27:49 +0100
Subject: [PATCH 25/32] add a little changes for search action

---
 mdk/share/python/miro2/core/node_action.py | 42 +++++++++++++++++++++-
 1 file changed, 41 insertions(+), 1 deletion(-)

diff --git a/mdk/share/python/miro2/core/node_action.py b/mdk/share/python/miro2/core/node_action.py
index 73e1143..80fbb4a 100644
--- a/mdk/share/python/miro2/core/node_action.py
+++ b/mdk/share/python/miro2/core/node_action.py
@@ -47,6 +47,10 @@
 from action.action_avert import ActionAvert
 from action.action_retreat import ActionRetreat
 
+from action.action_search import ActionSearch
+from random import choice
+
+
 from std_msgs.msg import MultiArrayDimension
 
 
@@ -71,7 +75,8 @@ def __init__(self, sys):
 				ActionApproach(self),
 				ActionAvert(self),
 				ActionFlee(self),
-				ActionRetreat(self)
+				ActionRetreat(self),
+				ActionSearch(self)
 				]
 
 		# state
@@ -298,6 +303,38 @@ def start_test_action(self, action_name):
 			if self.count > start_at and self.selector.selected == 0:
 				self.state.keep_running = False
 
+	# debug search action for test ~lucy
+	def testSearch(self, action_name):
+		action_name = "search"
+		random_action = ['RIGHT','PUSH','LEFT'] 	# there are three search actions, choose randomly ~lucy
+		action = choice(random_action)
+
+		print "start test action", action_name
+		print "do chosen action", action
+
+		if action_name == "search":
+			if action=='RIGHT':
+				self.action_input.priority_peak.height = 1
+				self.action_input.priority_peak.size = 0.005
+				self.action_input.priority_peak.azim = 1.57
+				self.action_input.priority_peak.elev = 0.0
+				self.action_input.priority_peak.size_norm = 0.5
+				self.action_input.priority_peak.range = 1.0
+			elif action=='PUSH':
+				self.action_input.priority_peak.height = 1
+				self.action_input.priority_peak.size = 0.005
+				self.action_input.priority_peak.azim = 1.57
+				self.action_input.priority_peak.elev = 0.0
+				self.action_input.priority_peak.size_norm = 0.5
+				self.action_input.priority_peak.range = 1.0
+			else:
+				self.action_input.priority_peak.height = 1
+				self.action_input.priority_peak.size = 0.005
+				self.action_input.priority_peak.azim = 1.57
+				self.action_input.priority_peak.elev = 0.0
+				self.action_input.priority_peak.size_norm = 0.5
+				self.action_input.priority_peak.range = 1.0
+
 	def tick(self):
 
 		# cannot usefully proceed without this
@@ -326,6 +363,9 @@ def tick(self):
 		if self.pars.flags.DEV_RUN_TEST_ACTION:
 			self.start_test_action()
 
+		# do search action for test ~lucy
+		self.testSearch()
+
 		# update selection mechanism
 		self.selector.update(self.actions)
 

From 8057049229fb83ee07599cbcb92174ecf8af27f9 Mon Sep 17 00:00:00 2001
From: YaKuRei <827752559@qq.com>
Date: Mon, 16 Sep 2019 16:57:45 +0100
Subject: [PATCH 26/32] update for test

---
 mdk/share/python/miro2/core/node_action.py | 21 ++++++++++++++-------
 1 file changed, 14 insertions(+), 7 deletions(-)

diff --git a/mdk/share/python/miro2/core/node_action.py b/mdk/share/python/miro2/core/node_action.py
index 80fbb4a..7754cba 100644
--- a/mdk/share/python/miro2/core/node_action.py
+++ b/mdk/share/python/miro2/core/node_action.py
@@ -306,9 +306,11 @@ def start_test_action(self, action_name):
 	# debug search action for test ~lucy
 	def testSearch(self, action_name):
 		action_name = "search"
-		random_action = ['RIGHT','PUSH','LEFT'] 	# there are three search actions, choose randomly ~lucy
+		random_action = ['RIGHT','PUSH','LEFT'] # there are three search actions, choose randomly, using left camera ~lucy
 		action = choice(random_action)
 
+		action = 'PUSH'
+
 		print "start test action", action_name
 		print "do chosen action", action
 
@@ -316,25 +318,30 @@ def testSearch(self, action_name):
 			if action=='RIGHT':
 				self.action_input.priority_peak.height = 1
 				self.action_input.priority_peak.size = 0.005
-				self.action_input.priority_peak.azim = 1.57
-				self.action_input.priority_peak.elev = 0.0
+				self.action_input.priority_peak.azim = -0.267970103903
+				self.action_input.priority_peak.elev = 0.493885703773
 				self.action_input.priority_peak.size_norm = 0.5
 				self.action_input.priority_peak.range = 1.0
 			elif action=='PUSH':
 				self.action_input.priority_peak.height = 1
 				self.action_input.priority_peak.size = 0.005
-				self.action_input.priority_peak.azim = 1.57
-				self.action_input.priority_peak.elev = 0.0
+				self.action_input.priority_peak.azim = -0.105382544279
+				self.action_input.priority_peak.elev = 0.508092899383
 				self.action_input.priority_peak.size_norm = 0.5
 				self.action_input.priority_peak.range = 1.0
 			else:
 				self.action_input.priority_peak.height = 1
 				self.action_input.priority_peak.size = 0.005
-				self.action_input.priority_peak.azim = 1.57
-				self.action_input.priority_peak.elev = 0.0
+				self.action_input.priority_peak.azim = 0.962490328192
+				self.action_input.priority_peak.elev = 0.5524675532
 				self.action_input.priority_peak.size_norm = 0.5
 				self.action_input.priority_peak.range = 1.0
 
+		for action in self.actions:
+			if action.name == action_name:
+				action.interface.priority = 1.0
+				return
+
 	def tick(self):
 
 		# cannot usefully proceed without this

From 97f68396db81b1003c9360e86a7c8217ff37356e Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Mon, 16 Sep 2019 18:17:23 +0100
Subject: [PATCH 27/32] update

---
 mdk/share/python/miro2/core/node_action.py | 65 ++++++++++++----------
 1 file changed, 37 insertions(+), 28 deletions(-)

diff --git a/mdk/share/python/miro2/core/node_action.py b/mdk/share/python/miro2/core/node_action.py
index 7754cba..7d29c49 100644
--- a/mdk/share/python/miro2/core/node_action.py
+++ b/mdk/share/python/miro2/core/node_action.py
@@ -304,43 +304,52 @@ def start_test_action(self, action_name):
 				self.state.keep_running = False
 
 	# debug search action for test ~lucy
-	def testSearch(self, action_name):
+	def testSearch(self):
 		action_name = "search"
 		random_action = ['RIGHT','PUSH','LEFT'] # there are three search actions, choose randomly, using left camera ~lucy
 		action = choice(random_action)
 
-		action = 'PUSH'
+		action = 'LEFT'
 
 		print "start test action", action_name
 		print "do chosen action", action
 
-		if action_name == "search":
-			if action=='RIGHT':
-				self.action_input.priority_peak.height = 1
-				self.action_input.priority_peak.size = 0.005
-				self.action_input.priority_peak.azim = -0.267970103903
-				self.action_input.priority_peak.elev = 0.493885703773
-				self.action_input.priority_peak.size_norm = 0.5
-				self.action_input.priority_peak.range = 1.0
-			elif action=='PUSH':
-				self.action_input.priority_peak.height = 1
-				self.action_input.priority_peak.size = 0.005
-				self.action_input.priority_peak.azim = -0.105382544279
-				self.action_input.priority_peak.elev = 0.508092899383
-				self.action_input.priority_peak.size_norm = 0.5
-				self.action_input.priority_peak.range = 1.0
-			else:
-				self.action_input.priority_peak.height = 1
-				self.action_input.priority_peak.size = 0.005
-				self.action_input.priority_peak.azim = 0.962490328192
-				self.action_input.priority_peak.elev = 0.5524675532
-				self.action_input.priority_peak.size_norm = 0.5
-				self.action_input.priority_peak.range = 1.0
+		start_at = 100
+		if self.count == start_at:
 
-		for action in self.actions:
-			if action.name == action_name:
-				action.interface.priority = 1.0
-				return
+			if action_name == "search":
+				if action=='RIGHT':
+					self.action_input.priority_peak.height = 1
+					self.action_input.priority_peak.size = 0.005
+					self.action_input.priority_peak.azim = -1.37611842787
+					self.action_input.priority_peak.elev = 0.22428584479
+					self.action_input.priority_peak.size_norm = 0.5
+					self.action_input.priority_peak.range = 1.0
+				elif action=='PUSH':
+					self.action_input.priority_peak.height = 1
+					self.action_input.priority_peak.size = 0.005
+					self.action_input.priority_peak.azim = -0.105382544279
+					self.action_input.priority_peak.elev = 0.508092899383
+					self.action_input.priority_peak.size_norm = 0.5
+					self.action_input.priority_peak.range = 1.0
+				elif action=='LEFT':
+					self.action_input.priority_peak.height = 1
+					self.action_input.priority_peak.size = 0.005
+					self.action_input.priority_peak.azim = 0.962490328192
+					self.action_input.priority_peak.elev = 0.5524675532
+					self.action_input.priority_peak.size_norm = 0.5
+					self.action_input.priority_peak.range = 1.0
+
+			for action in self.actions:
+				if action.name == action_name:
+					action.interface.priority = 1.0
+					return
+		else:
+
+			self.action_input.priority_peak.height = 0
+
+			if self.count > start_at and self.selector.selected == 0:
+				self.state.keep_running = False
 
 	def tick(self):
 

From 0041a8df8c4d42dfbb1784808543910bfaba18c2 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Mon, 16 Sep 2019 23:06:18 +0100
Subject: [PATCH 28/32] 2

---
 mdk/share/python/miro2/core/action/action_search.py |  2 ++
 mdk/share/python/miro2/core/node_action.py          | 12 ++++++------
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/mdk/share/python/miro2/core/action/action_search.py b/mdk/share/python/miro2/core/action/action_search.py
index e76d5f4..4a6730e 100644
--- a/mdk/share/python/miro2/core/action/action_search.py
+++ b/mdk/share/python/miro2/core/action/action_search.py
@@ -134,6 +134,8 @@ def start(self):
 
     def service(self):
 
+        print "doing Action Search"
+
         # read clock
         x = self.clock.cosine_profile()
         self.clock.advance(True)
diff --git a/mdk/share/python/miro2/core/node_action.py b/mdk/share/python/miro2/core/node_action.py
index 7d29c49..2a6deaf 100644
--- a/mdk/share/python/miro2/core/node_action.py
+++ b/mdk/share/python/miro2/core/node_action.py
@@ -321,22 +321,22 @@ def testSearch(self):
 				if action=='RIGHT':
 					self.action_input.priority_peak.height = 1
 					self.action_input.priority_peak.size = 0.005
-					self.action_input.priority_peak.azim = -1.37611842787
-					self.action_input.priority_peak.elev = 0.22428584479
+					self.action_input.priority_peak.azim = -1.44547299744
+					self.action_input.priority_peak.elev = 0.39029874673
 					self.action_input.priority_peak.size_norm = 0.5
 					self.action_input.priority_peak.range = 1.0
 				elif action=='PUSH':
 					self.action_input.priority_peak.height = 1
 					self.action_input.priority_peak.size = 0.005
-					self.action_input.priority_peak.azim = -0.105382544279
-					self.action_input.priority_peak.elev = 0.508092899383
+					self.action_input.priority_peak.azim = 0.056516230312
+					self.action_input.priority_peak.elev = 0.370701502705
 					self.action_input.priority_peak.size_norm = 0.5
 					self.action_input.priority_peak.range = 1.0
 				elif action=='LEFT':
 					self.action_input.priority_peak.height = 1
 					self.action_input.priority_peak.size = 0.005
-					self.action_input.priority_peak.azim = 0.962490328192
-					self.action_input.priority_peak.elev = 0.5524675532
+					self.action_input.priority_peak.azim = 1.31007518607
+					self.action_input.priority_peak.elev = 0.471882843261
 					self.action_input.priority_peak.size_norm = 0.5
 					self.action_input.priority_peak.range = 1.0
 

From 88b71840c801e7f3426f742e5b4aa5f58cf935f3 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Mon, 16 Sep 2019 23:17:22 +0100
Subject: [PATCH 29/32] update

---
 mdk/share/python/miro2/core/node_action.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/mdk/share/python/miro2/core/node_action.py b/mdk/share/python/miro2/core/node_action.py
index 2a6deaf..0fc757d 100644
--- a/mdk/share/python/miro2/core/node_action.py
+++ b/mdk/share/python/miro2/core/node_action.py
@@ -309,7 +309,7 @@ def testSearch(self):
 		random_action = ['RIGHT','PUSH','LEFT'] # there are three search actions, choose randomly, using left camera ~lucy
 		action = choice(random_action)
 
-		action = 'LEFT'
+		# action = 'RIGHT'
 
 		print "start test action", action_name
 		print "do chosen action", action
@@ -318,7 +318,7 @@ def testSearch(self):
 		if self.count == start_at:
 
 			if action_name == "search":
-				if action=='RIGHT':
+				if action=='LEFT':
 					self.action_input.priority_peak.height = 1
 					self.action_input.priority_peak.size = 0.005
 					self.action_input.priority_peak.azim = -1.44547299744
@@ -332,7 +332,7 @@ def testSearch(self):
 					self.action_input.priority_peak.elev = 0.370701502705
 					self.action_input.priority_peak.size_norm = 0.5
 					self.action_input.priority_peak.range = 1.0
-				elif action=='LEFT':
+				elif action=='RIGHT':
 					self.action_input.priority_peak.height = 1
 					self.action_input.priority_peak.size = 0.005
 					self.action_input.priority_peak.azim = 1.31007518607

From ad6c2233632b42af55c3eab8666d43d32ccf7113 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Tue, 17 Sep 2019 01:18:15 +0100
Subject: [PATCH 30/32] update search action

---
 .../python/miro2/core/action/action_search.py |  9 +--
 .../python/miro2/core/action/basal_ganglia.py |  2 +
 mdk/share/python/miro2/core/node_action.py    | 77 ++++++++++---------
 3 files changed, 44 insertions(+), 44 deletions(-)

diff --git a/mdk/share/python/miro2/core/action/action_search.py b/mdk/share/python/miro2/core/action/action_search.py
index 4a6730e..228f205 100644
--- a/mdk/share/python/miro2/core/action/action_search.py
+++ b/mdk/share/python/miro2/core/action/action_search.py
@@ -86,7 +86,7 @@ def compute_priority(self):
 
     def event_start(self):
 
-        self.appetitive_response(self.pars.action.approach_appetitive_commitment)
+        # self.appetitive_response(self.pars.action.approach_appetitive_commitment)
         self.debug_event_start()
 
     def start(self):
@@ -135,7 +135,7 @@ def start(self):
     def service(self):
 
         print "doing Action Search"
-
+        print  'searchActionLoop',self.input.priority_peak.azim
         # read clock
         x = self.clock.cosine_profile()
         self.clock.advance(True)
@@ -151,7 +151,4 @@ def service(self):
 
         # debug fovea movement through WORLD
         #fovea_WORLD = self.kc.changeFrameAbs(miro.constants.LINK_HEAD, miro.constants.LINK_WORLD, self.fovea_HEAD)
-        #print "fovea_WORLD", fovea_WORLD, self.clock.toString()
-
-
-
+        #print "fovea_WORLD", fovea_WORLD, self.clock.toString()
\ No newline at end of file
diff --git a/mdk/share/python/miro2/core/action/basal_ganglia.py b/mdk/share/python/miro2/core/action/basal_ganglia.py
index 44fa5fe..63121b4 100644
--- a/mdk/share/python/miro2/core/action/basal_ganglia.py
+++ b/mdk/share/python/miro2/core/action/basal_ganglia.py
@@ -92,6 +92,8 @@ def update(self, actions):
 		# Select action with maximum priority (winner take all)
 		selected = np.argmax(self.prio)
 
+		print "\n[**** SELECT", actions[selected].name, "??????"
+
 		# update selection
 		if self.selected != selected:
 			print "\n[**** SELECT ACTION", actions[selected].name, "****]"
diff --git a/mdk/share/python/miro2/core/node_action.py b/mdk/share/python/miro2/core/node_action.py
index 0fc757d..a8ca6f3 100644
--- a/mdk/share/python/miro2/core/node_action.py
+++ b/mdk/share/python/miro2/core/node_action.py
@@ -309,47 +309,46 @@ def testSearch(self):
 		random_action = ['RIGHT','PUSH','LEFT'] # there are three search actions, choose randomly, using left camera ~lucy
 		action = choice(random_action)
 
-		# action = 'RIGHT'
+		# action = 'PUSH'
 
-		print "start test action", action_name
-		print "do chosen action", action
 
-		start_at = 100
-		if self.count == start_at:
-
-			if action_name == "search":
-				if action=='LEFT':
-					self.action_input.priority_peak.height = 1
-					self.action_input.priority_peak.size = 0.005
-					self.action_input.priority_peak.azim = -1.44547299744
-					self.action_input.priority_peak.elev = 0.39029874673
-					self.action_input.priority_peak.size_norm = 0.5
-					self.action_input.priority_peak.range = 1.0
-				elif action=='PUSH':
-					self.action_input.priority_peak.height = 1
-					self.action_input.priority_peak.size = 0.005
-					self.action_input.priority_peak.azim = 0.056516230312
-					self.action_input.priority_peak.elev = 0.370701502705
-					self.action_input.priority_peak.size_norm = 0.5
-					self.action_input.priority_peak.range = 1.0
-				elif action=='RIGHT':
-					self.action_input.priority_peak.height = 1
-					self.action_input.priority_peak.size = 0.005
-					self.action_input.priority_peak.azim = 1.31007518607
-					self.action_input.priority_peak.elev = 0.471882843261
-					self.action_input.priority_peak.size_norm = 0.5
-					self.action_input.priority_peak.range = 1.0
-
-			for action in self.actions:
-				if action.name == action_name:
-					action.interface.priority = 1.0
-					return
-		else:
+		if action_name == "search":
+			print "start test action", action_name
+			print "do chosen action", action
 
-			self.action_input.priority_peak.height = 0
+			if action=='RIGHT':
+				self.action_input.priority_peak.height = 1
+				self.action_input.priority_peak.size = 0.005
+				self.action_input.priority_peak.azim = -1.44547299744
+				self.action_input.priority_peak.elev = 0.39029874673
+				self.action_input.priority_peak.size_norm = 0.5
+				self.action_input.priority_peak.range = 1.0
+				print 'update',self.action_input.priority_peak.azim
+			elif action=='PUSH':
+				self.action_input.priority_peak.height = 1
+				self.action_input.priority_peak.size = 0.005
+				self.action_input.priority_peak.azim = 0.056516230312
+				self.action_input.priority_peak.elev = 0.370701502705
+				self.action_input.priority_peak.size_norm = 0.5
+				self.action_input.priority_peak.range = 1.0
+			elif action=='LEFT':
+				self.action_input.priority_peak.height = 1
+				self.action_input.priority_peak.size = 0.005
+				self.action_input.priority_peak.azim = 1.31007518607
+				self.action_input.priority_peak.elev = 0.471882843261
+				self.action_input.priority_peak.size_norm = 0.5
+				self.action_input.priority_peak.range = 1.0
 
-			if self.count > start_at and self.selector.selected == 0:
-				self.state.keep_running = False
+		for action in self.actions:
+			if action.name == action_name:
+				action.interface.priority = 1.0
+				return
+		# else:
+		#
+		# 	self.action_input.priority_peak.height = 0
+		#
+		# 	if self.count > start_at and self.selector.selected == 0:
+		# 		self.state.keep_running = False
 
 	def tick(self):
 
@@ -379,9 +378,11 @@ def tick(self):
 		if self.pars.flags.DEV_RUN_TEST_ACTION:
 			self.start_test_action()
 
+		print "name!!!!", self.selector.selected
 		# do search action for test ~lucy
+		# if self.actions[self.selector.selected].name=='search':
 		self.testSearch()
-
+		print 'current',self.state.priority_peak.azim
 		# update selection mechanism
 		self.selector.update(self.actions)
 

From 3cbeb61537174f8f3078b2bd44b067eca9174115 Mon Sep 17 00:00:00 2001
From: YaKuRei <827752559@qq.com>
Date: Wed, 18 Sep 2019 02:24:04 +0200
Subject: [PATCH 31/32] add priority calculation in search

---
 .../python/miro2/core/action/action_search.py | 31 ++++++++++++-------
 mdk/share/python/miro2/core/pars.py           |  7 +++++
 2 files changed, 26 insertions(+), 12 deletions(-)

diff --git a/mdk/share/python/miro2/core/action/action_search.py b/mdk/share/python/miro2/core/action/action_search.py
index 228f205..6c73bea 100644
--- a/mdk/share/python/miro2/core/action/action_search.py
+++ b/mdk/share/python/miro2/core/action/action_search.py
@@ -62,27 +62,34 @@ def compute_priority(self):
         fixation = self.input.fixation
 
         # extract pars
-        base_priority = self.pars.action.approach_base_prio
-        size_gain = self.pars.action.approach_size_gain
-        arousal_gain = self.pars.action.approach_arousal_gain
-        valence_gain = self.pars.action.approach_valence_gain
-        fixation_gain = self.pars.action.approach_fixation_gain
+        base_prio = self.pars.action.search_base_prio
+        arousal_gain = self.pars.action.search_arousal_gain
+        valence_gain = self.pars.action.search_valence_gain
+        size_gain = self.pars.action.search_size_gain
+        fixation_gain = self.pars.action.search_fixation_gain
 
         # compute priority
-        tend_some = np.tanh(arousal_gain * (arousal - 0.5) + fixation_gain * (fixation - 0.5))
-        tend_appe = np.tanh(valence_gain * (valence - 0.5) - size_gain * (size_norm - 0.5))
-        priority = height * (base_priority + tend_some + tend_appe)
+        priority = height * (base_prio
+                             - valence_gain * (valence - 0.5)
+                             + arousal_gain * (arousal - 0.5)
+                             + fixation_gain * (fixation - 0.5)
+                             + size_gain * size_norm)
 
-        # modulate by cliff and sonar
-        priority *= self.input.conf_surf
-        priority *= self.input.conf_space
+        # # modulate by cliff and sonar
+        # priority *= self.input.conf_surf
+        # priority *= self.input.conf_space
 
         # modulate for dev
         if self.pars.flags.DEV_ORIENT_ONLY:
             priority = 0.0
 
+        # modulate for flag of seeing master ~lucy
+        if self.pars.flags.SEE_MASTER:
+            priority = 0.0
+
         # ok set the max priority, then we can only do search action and test it ~lucy
-        return self.pars.action.priority_uninterruptable  #priority
+        # return self.pars.action.priority_uninterruptable
+        return priority
 
     def event_start(self):
 
diff --git a/mdk/share/python/miro2/core/pars.py b/mdk/share/python/miro2/core/pars.py
index 76d9308..30a6d3e 100644
--- a/mdk/share/python/miro2/core/pars.py
+++ b/mdk/share/python/miro2/core/pars.py
@@ -264,6 +264,13 @@ def __init__(self):
 		self.flee_min_steps = 50
 		self.flee_max_steps = 300
 
+		# set parameters of priority in search action ~lucy copy from flee need to be modified
+		self.search_base_prio = -0.1
+		self.search_fixation_gain = 0.0
+		self.search_arousal_gain = 0.25
+		self.search_valence_gain = 0.5
+		self.search_size_gain = 0.0
+
 		self.avert_base_prio = 0.0
 
 		self.retreat_distance_m = 0.6

From 741dd625d4bd2753dd40946fb2c64fbe4249aef1 Mon Sep 17 00:00:00 2001
From: jodie528 <liws18uk@yeah.net>
Date: Thu, 26 Sep 2019 00:19:12 +0100
Subject: [PATCH 32/32] uodate

---
 Client_weishi/detect_primary_user.py          |  2 +
 .../python/miro2/core/action/action_flee.py   |  1 +
 .../python/miro2/core/action/action_halt.py   |  1 +
 .../python/miro2/core/action/action_search.py |  5 +
 .../python/miro2/core/action/basal_ganglia.py |  2 +-
 mdk/share/python/miro2/core/client_demo.py    | 74 ++++++++++++---
 mdk/share/python/miro2/core/node_action.py    | 22 ++---
 .../python/miro2/core/node_detect_face.py     | 16 ++--
 .../miro2/core/node_face_recognition.py       | 26 +++++-
 mdk/share/python/miro2/core/node_spatial.py   | 93 ++++++++++++++++---
 10 files changed, 199 insertions(+), 43 deletions(-)

diff --git a/Client_weishi/detect_primary_user.py b/Client_weishi/detect_primary_user.py
index ef3cadd..0f076d1 100644
--- a/Client_weishi/detect_primary_user.py
+++ b/Client_weishi/detect_primary_user.py
@@ -32,6 +32,7 @@ def face_detection (self, image):
                 # face_x_coord = x + w / 2
                 # face_y_coord = y + h / 2
                 roi_color = image[y:y + h, x:x + w]
+                print('======roi_color', roi_color)
                 dic_faces[face] = [roi_color, [x, y, w, h]]
                 face += 1
 
@@ -61,6 +62,7 @@ def face_recognition(self, dic_faces):
 
         for key, value in dic_faces.items():
             face = value[0]
+            print('------', face)
 
             array = cv2.cvtColor(np.array(face), cv2.COLOR_RGB2BGR)
             image = Image.fromarray(array)
diff --git a/mdk/share/python/miro2/core/action/action_flee.py b/mdk/share/python/miro2/core/action/action_flee.py
index 5494157..249dc0b 100644
--- a/mdk/share/python/miro2/core/action/action_flee.py
+++ b/mdk/share/python/miro2/core/action/action_flee.py
@@ -85,6 +85,7 @@ def compute_priority(self):
 		if self.pars.flags.DEV_ORIENT_ONLY:
 			priority = 0.0
 
+
 		# ok
 		return priority
 
diff --git a/mdk/share/python/miro2/core/action/action_halt.py b/mdk/share/python/miro2/core/action/action_halt.py
index 68b9d16..5939000 100644
--- a/mdk/share/python/miro2/core/action/action_halt.py
+++ b/mdk/share/python/miro2/core/action/action_halt.py
@@ -141,6 +141,7 @@ def compute_priority(self):
 
 		# stall?
 		if self.pars.flags.ACTION_HALT_ON_STALL and stalled:
+			print "halt", self.pars.action.priority_high
 			return self.pars.action.priority_high
 
 		# no stall
diff --git a/mdk/share/python/miro2/core/action/action_search.py b/mdk/share/python/miro2/core/action/action_search.py
index 6c73bea..81533d8 100644
--- a/mdk/share/python/miro2/core/action/action_search.py
+++ b/mdk/share/python/miro2/core/action/action_search.py
@@ -83,6 +83,10 @@ def compute_priority(self):
         if self.pars.flags.DEV_ORIENT_ONLY:
             priority = 0.0
 
+<<<<<<< HEAD
+        return self.pars.action.priority_uninterruptable  #priority
+        #return 0
+=======
         # modulate for flag of seeing master ~lucy
         if self.pars.flags.SEE_MASTER:
             priority = 0.0
@@ -90,6 +94,7 @@ def compute_priority(self):
         # ok set the max priority, then we can only do search action and test it ~lucy
         # return self.pars.action.priority_uninterruptable
         return priority
+>>>>>>> 3cbeb61537174f8f3078b2bd44b067eca9174115
 
     def event_start(self):
 
diff --git a/mdk/share/python/miro2/core/action/basal_ganglia.py b/mdk/share/python/miro2/core/action/basal_ganglia.py
index 63121b4..dc092c6 100644
--- a/mdk/share/python/miro2/core/action/basal_ganglia.py
+++ b/mdk/share/python/miro2/core/action/basal_ganglia.py
@@ -92,7 +92,7 @@ def update(self, actions):
 		# Select action with maximum priority (winner take all)
 		selected = np.argmax(self.prio)
 
-		print "\n[**** SELECT", actions[selected].name, "??????"
+		# print "\n[**** SELECT", actions[selected].name, "??????"
 
 		# update selection
 		if self.selected != selected:
diff --git a/mdk/share/python/miro2/core/client_demo.py b/mdk/share/python/miro2/core/client_demo.py
index c524359..f2b2d77 100755
--- a/mdk/share/python/miro2/core/client_demo.py
+++ b/mdk/share/python/miro2/core/client_demo.py
@@ -144,6 +144,8 @@ def __init__(self, pars):
 		# detect_face [faces_coordinate, image]
 		self.detect_face = [None, None]
 		self.primary_user = False
+		# [user_flag , coordinate of face] = [Ture/False, (x,y,w,h)]
+		self.face_saliences = [None, None]
 
 		# internal
 		self.reconfigure_cameras = False
@@ -183,28 +185,31 @@ def instantiate(self, sys):
 
 		# instantiate
 		if self.client_type == "camera":
+			self.lower = NodeLower(sys)
+			self.affect = NodeAffect(sys)
+			self.express = NodeExpress(sys)
+			self.action = NodeAction(sys)
+			self.loop = NodeLoop(sys)
+			self.spatial = NodeSpatial(sys)
+
 			self.decode = NodeDecode(sys)
 			self.detect_motion = NodeDetectMotion(sys)
 			self.detect_face = NodeDetectFace(sys)
-		#	self.face_recognition = NodeFaceRecognition(sys)
+			self.face_recognition = NodeFaceRecognition(sys)
 			self.detect_ball = NodeDetectBall(sys)
 
+
 		# instantiate
 		if self.client_type == "mics":
 			self.detect_audio = NodeDetectAudio(sys)
 
 
-		# # instantiate
-		# if self.client_type == "recognition":
-		# 	self.decode = NodeDecode(sys)
-		# 	self.detect_face = NodeDetectFace(sys)
-
 
 
 	def tick(self):
 
 		# tick
-		if self.client_type == "main":
+		if self.client_type == "camera":
 			self.lower.tick()
 			self.affect.tick()
 			self.express.tick()
@@ -301,6 +306,42 @@ def __init__(self, client_type):
 		# select client type
 		if self.client_type == "camera":
 
+			# publish priority
+			self.pub_pri = [
+				self.publish('core/pril', sensor_msgs.msg.Image),
+				self.publish('core/prir', sensor_msgs.msg.Image),
+				self.publish('core/priw', sensor_msgs.msg.Image)
+			]
+
+			# publish control outputs
+			self.pub_cos = self.publish('control/cosmetic_joints', std_msgs.msg.Float32MultiArray)
+			self.pub_illum = self.publish('control/illum', std_msgs.msg.UInt32MultiArray)
+
+			# publish core states
+			self.pub_affect_state = self.publish('core/affect/state', miro.msg.affect_state)
+			self.pub_affect_time = self.publish('core/affect/time', std_msgs.msg.UInt32)
+			self.pub_sel_prio = self.publish('core/selection/priority', std_msgs.msg.Float32MultiArray)
+			self.pub_sel_inhib = self.publish('core/selection/inhibition', std_msgs.msg.Float32MultiArray)
+
+			# reference core states output messages in output array
+			self.output.affect_state = self.pub_affect_state.msg
+			self.output.affect_time = self.pub_affect_time.msg
+			self.output.sel_prio = self.pub_sel_prio.msg
+			self.output.sel_inhib = self.pub_sel_inhib.msg
+
+			# publish
+			self.pub_flags = self.publish('control/flags', std_msgs.msg.UInt32)
+			self.pub_tone = self.publish('control/tone', std_msgs.msg.UInt16MultiArray)
+
+			# publish motor output
+			if self.use_external_kc:
+				self.pub_push = self.publish('core/mpg/push', miro.msg.push)
+				self.pub_reset = self.publish('core/mpg/reset', std_msgs.msg.UInt32)
+			else:
+				self.pub_kin = self.publish('control/kinematic_joints', sensor_msgs.msg.JointState)
+				self.pub_kin.msg.name = ['tilt', 'lift', 'yaw', 'pitch']
+				self.pub_cmd_vel = self.publish('control/cmd_vel', geometry_msgs.msg.TwistStamped)
+
 			# publish motion detector output
 			self.pub_mov = self.publish('core/mov' + self.camera_sub, sensor_msgs.msg.Image)
 
@@ -355,6 +396,17 @@ def __init__(self, client_type):
 		# select client type
 		if self.client_type == "camera":
 
+			# subscribe
+			self.subscribe('sensors/package', miro.msg.sensors_package, self.callback_sensors_package)
+			self.subscribe('core/voice_state', miro.msg.voice_state, self.callback_voice_state)
+			self.subscribe('core/detect_face_l', std_msgs.msg.Float32MultiArray, self.callback_detect_face)
+			self.subscribe('core/detect_face_r', std_msgs.msg.Float32MultiArray, self.callback_detect_face)
+			self.subscribe('core/detect_ball_l', std_msgs.msg.UInt16MultiArray, self.callback_detect_ball)
+			self.subscribe('core/detect_ball_r', std_msgs.msg.UInt16MultiArray, self.callback_detect_ball)
+			self.subscribe('core/audio_event', std_msgs.msg.Float32MultiArray, self.callback_audio_event)
+			self.subscribe('core/movl', sensor_msgs.msg.Image, self.callback_movl)
+			self.subscribe('core/movr', sensor_msgs.msg.Image, self.callback_movr)
+
 			# subscribe
 			self.subscribe('sensors/cam' + self.camera_sub + '/compressed', sensor_msgs.msg.CompressedImage, self.callback_cam)
 			self.subscribe('core/affect/state', miro.msg.affect_state, self.callback_affect_state)
@@ -371,7 +423,7 @@ def __init__(self, client_type):
 		time.sleep(1)
 
 		# select client type
-		if self.client_type == "main":
+		if self.client_type == "camera":
 
 			# reset body (dev only)
 			if self.use_external_kc:
@@ -526,7 +578,7 @@ def callback_detect_face(self, msg):
 		while i < len(x):
 			faces.append(x[i:i+5])
 			i += 5
-		self.state.detect_face[stream_index] = faces
+		# self.state.detect_face[stream_index] = faces
 
 	def callback_detect_ball(self, msg):
 
@@ -564,7 +616,7 @@ def callback_movr(self, msg):
 		self.callback_mov(1, msg)
 
 	def callback_cam(self, msg):
-		#print('callback camera')
+		# print('callback camera')
 
 		stream_index = self.stream_index
 
@@ -604,7 +656,7 @@ def callback_cam(self, msg):
 		# tick
 		self.nodes.detect_motion.tick_camera(stream_index)
 		self.nodes.detect_face.tick_camera(stream_index)
-		# self.nodes.face_recognition.tick_camera(stream_index)
+		self.nodes.face_recognition.tick_camera(stream_index)
 		self.nodes.detect_ball.tick_camera(stream_index)
 
 		# publish result
diff --git a/mdk/share/python/miro2/core/node_action.py b/mdk/share/python/miro2/core/node_action.py
index a8ca6f3..ffe7f55 100644
--- a/mdk/share/python/miro2/core/node_action.py
+++ b/mdk/share/python/miro2/core/node_action.py
@@ -303,10 +303,9 @@ def start_test_action(self, action_name):
 			if self.count > start_at and self.selector.selected == 0:
 				self.state.keep_running = False
 
-	# debug search action for test ~lucy
 	def testSearch(self):
 		action_name = "search"
-		random_action = ['RIGHT','PUSH','LEFT'] # there are three search actions, choose randomly, using left camera ~lucy
+		random_action = ['RIGHT','PUSH','LEFT'] # there are three search actions, choose randomly, using left camera
 		action = choice(random_action)
 
 		# action = 'PUSH'
@@ -339,10 +338,10 @@ def testSearch(self):
 				self.action_input.priority_peak.size_norm = 0.5
 				self.action_input.priority_peak.range = 1.0
 
-		for action in self.actions:
-			if action.name == action_name:
-				action.interface.priority = 1.0
-				return
+		# for action in self.actions:
+		# 	if action.name == action_name:
+		# 		action.interface.priority = 1.0
+		# 		return
 		# else:
 		#
 		# 	self.action_input.priority_peak.height = 0
@@ -378,11 +377,12 @@ def tick(self):
 		if self.pars.flags.DEV_RUN_TEST_ACTION:
 			self.start_test_action()
 
-		print "name!!!!", self.selector.selected
-		# do search action for test ~lucy
-		# if self.actions[self.selector.selected].name=='search':
-		self.testSearch()
-		print 'current',self.state.priority_peak.azim
+		# print "name!!!!", self.selector.selected
+		# do search action for test
+		if self.actions[self.selector.selected].name=='search':
+			print("????????????????")
+			self.testSearch()
+		# print 'current',self.state.priority_peak.azim
 		# update selection mechanism
 		self.selector.update(self.actions)
 
diff --git a/mdk/share/python/miro2/core/node_detect_face.py b/mdk/share/python/miro2/core/node_detect_face.py
index 2e78419..939eb6f 100644
--- a/mdk/share/python/miro2/core/node_detect_face.py
+++ b/mdk/share/python/miro2/core/node_detect_face.py
@@ -74,10 +74,10 @@ def __init__(self, sys):
 		self.ticks = [0, 0]
 
 	def tick_camera(self, stream_index):
-
 		# get image (grayscale)
 		img = self.state.frame_gry[stream_index]
 
+
 		# img_roi = self.state.frame_raw[stream_index]
 		#-----------------------------
 		# cv2.imshow('face', img_roi)
@@ -106,6 +106,12 @@ def tick_camera(self, stream_index):
 					#print "detected face", stream_index, conf, rect
 					face = np.concatenate((rect, conf))
 					faces.append(face)
+				# --------------------------
+				# x,y,w,h,conf = face
+				# cv2.rectangle(img, (int(x), int(y)), (int(x) + int(w), int(y) + int(h)), (255, 0, 0), 2)
+				# cv2.imshow("detected face", img)
+				# cv2.waitKey()
+				# cv2.destroyAllWindows()
 
 		# merge duplicates
 		# let's not do this for now, I'm not sure why it's needed yet
@@ -115,15 +121,13 @@ def tick_camera(self, stream_index):
 		self.state.detect_face[stream_index] = faces
 
 		# report face detected
-		if faces != []:
-			print 'detect face', faces
-			cv2.imshow('detected_face', faces)
-			cv2.waitKey(1)
+		# if faces != []:
+			# print 'detect face!!!!!', faces
 
 		# tick
 		self.ticks[stream_index] += 1
 		# -------------------------
-		cv2.destroyAllWindows()
+		# cv2.destroyAllWindows()
 
 	def merge_duplicates(self, faces):
 
diff --git a/mdk/share/python/miro2/core/node_face_recognition.py b/mdk/share/python/miro2/core/node_face_recognition.py
index 843e774..d5cff41 100644
--- a/mdk/share/python/miro2/core/node_face_recognition.py
+++ b/mdk/share/python/miro2/core/node_face_recognition.py
@@ -37,12 +37,22 @@ def tick_camera(self, stream_index):
         # faces is the array of detected faces from node_detect_face
         faces = self.state.detect_face[stream_index]
         img = self.state.frame_raw[stream_index]
-
+        # print('img:', img)
+        # print('faces:', faces)
+        face_salience = []
         for face in faces:
+            self.state.primary_user = False
+            face_ori = face
+            # print('face_ori', face_ori)
+
             (x, y, w, h, conf) = face
-            face = img[x:x+w, y:y+h]
+            face = img[y:y + h, x:x + w]
 
+            # --------------------------
+
+            # print('face: ',face)
             array = cv2.cvtColor(np.array(face), cv2.COLOR_RGB2BGR)
+            # print('array: ', array)
             image = Image.fromarray(array)
 
             # image convert to binary
@@ -60,6 +70,18 @@ def tick_camera(self, stream_index):
                 if len(response['FaceMatches']) > 0:
                     # store
                     self.state.primary_user = True
+                    cv2.rectangle(img, (int(x), int(y)), (int(x) + int(w), int(y) + int(h)), (0, 255, 0), 2)
                     print('=====FACE MATCH=====')
+                else:
+                    cv2.rectangle(img, (int(x), int(y)), (int(x) + int(w), int(y) + int(h)), (255, 0, 0), 2)
+
             except:
                 pass
+            face_salience.append((self.state.primary_user, face_ori))
+        self.state.face_saliences[stream_index] = face_salience
+        # cv2.imshow("detected face", img)
+        # cv2.waitKey()
+        # cv2.destroyAllWindows()
+
+
+
diff --git a/mdk/share/python/miro2/core/node_spatial.py b/mdk/share/python/miro2/core/node_spatial.py
index d156727..8d09f2f 100644
--- a/mdk/share/python/miro2/core/node_spatial.py
+++ b/mdk/share/python/miro2/core/node_spatial.py
@@ -388,6 +388,63 @@ def inject_audio(self, stream_index):
 			# inject
 			self.pri[stream_index] += (gain * 255.0 * audio_event.level) * response
 
+	def inject_primaryface(self, stream_index):
+
+		# extract and clear signal
+		face_saliences = self.state.face_saliences[stream_index]
+		self.state.face_saliences[stream_index] = None
+		counter = 0
+		# if signal is new
+		if not face_saliences is None:
+
+			for face_salience in face_saliences:
+				counter +=1
+				# extract
+				primary_user = face_salience[0]
+				rect = face_salience[1][0:4]
+				conf = face_salience[1][4]
+
+				print 'face_salience',face_salience
+				print 'primary_user',primary_user
+				print 'rect',rect
+				print 'conf',conf
+
+				# get range
+				range = self.estimate_range(face_salience[1][2], self.pars.action.face_size_m)
+
+				# debug
+				if not self.pars.flags.DEV_DEBUG_HALT: # do not pollute info
+					print "face at range", range, "with conf", conf
+				if self.pars.flags.DEV_DEBUG_DETECTION:
+					self.output.tone = 255
+
+				# paint in face
+				x = int(face_salience[1][0] + face_salience[1][2] * 0.5)
+				y = int(face_salience[1][1] + face_salience[1][3] * 0.5)
+				r = (face_salience[1][2] + face_salience[1][3]) * 0.25
+				if primary_user:
+					m = int(self.pars.spatial.face_gain * conf * 255.0)
+					print('=======================================================')
+					print("the salience value of primary user is : ", m)
+					print('=======================================================')
+				else:
+					m = int(0.6 * self.pars.spatial.face_gain * conf * 255.0)
+					print('=======================================================')
+					print("the salience value of non-primary user is : ", m)
+					print('=======================================================')
+
+				# choose radius that reflects representational size
+				# based on physical size in image
+				r = int(r * 0.5)
+
+				# inject stimulus
+				self.inject_dome(self.pri[stream_index], (x, y), r, m)
+
+				# store source
+				p = [x, y]
+				v = self.p2v(p, stream_index)
+				self.sources.append([0, v, range])
+				print "number of face", counter
 	def publish_peak(self, peak):
 
 		# attempt to lock
@@ -433,6 +490,10 @@ def find_stream_peak(self, stream_index):
 
 		# get image
 		img = self.pri[stream_index]
+		# print 'img', img
+		# cv2.imshow("salience map", img)
+		# cv2.waitKey()
+		# cv2.destroyAllWindows()
 
 		# find threshold for measuring size of priority region
 		height = float(img.max())
@@ -516,21 +577,24 @@ def process_stream(self, stream_index):
 		# for camera streams
 		if stream_index < 2:
 
-			# inject motion detector output
-			if self.pars.flags.SALIENCE_FROM_MOTION:
-				self.inject_motion(stream_index)
+			# # inject motion detector output
+			# if self.pars.flags.SALIENCE_FROM_MOTION:
+			# 	self.inject_motion(stream_index)
+			#
+			# # inject detected balls
+			# if self.pars.flags.SALIENCE_FROM_BALL:
+			# 	self.inject_ball(stream_index)
+			#
+			# # inject faces
+			# if self.pars.flags.SALIENCE_FROM_FACES:
+			# 	self.inject_face(stream_index)
 
-			# inject detected balls
-			if self.pars.flags.SALIENCE_FROM_BALL:
-				self.inject_ball(stream_index)
+			self.inject_primaryface(stream_index)
 
-			# inject faces
-			if self.pars.flags.SALIENCE_FROM_FACES:
-				self.inject_face(stream_index)
+		# # inject sound events
+		# if self.pars.flags.SALIENCE_FROM_SOUND:
+		# 	self.inject_audio(stream_index)
 
-		# inject sound events
-		if self.pars.flags.SALIENCE_FROM_SOUND:
-			self.inject_audio(stream_index)
 
 		# clip
 		self.pri[stream_index] = np.clip(self.pri[stream_index], 0, 255)
@@ -561,6 +625,7 @@ def process_stream(self, stream_index):
 		# publish priority map (mostly for debug)
 		self.state.frame_pri[stream_index] = self.pri[stream_index].astype(np.uint8)
 
+
 	def tick_camera(self, stream_index):
 
 		# return list of streams updated
@@ -590,6 +655,10 @@ def tick_camera(self, stream_index):
 			self.process_stream(2)
 			updated.append(2)
 
+		cv2.imshow("salience map", self.state.frame_pri[stream_index])
+		cv2.waitKey()
+		cv2.destroyAllWindows()
+
 		# ok
 		return updated