GS1Grader for UDI Vision Inspection

GS1Grader is a Python library for grading Data Matrix codes using GS1 quality metrics with modulation and symbol contrast implementation essential for UDI (Unique Device Identification) compliance in medical devices.

Prerequisites

Before installing GS1Grader, you need to install some system dependencies:

Ubuntu/Debian

sudo apt-get update
sudo apt-get install -y \
    libdmtx0b \
    ffmpeg \
    libsm6 \
    libxext6

Mac OS

# Install Homebrew if not already installed
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# Install the required dependencies
brew install libdmtx
brew install ffmpeg
brew install uv
brew install poetry

These system dependencies are required for proper functioning of OpenCV and pylibdmtx.

Installation with uv

create a virtual environment using uv and a suitable Python version (3.11 or higher):

uv venv .venv --python 3.11
source .venv/bin/activate

You can now install GS1Grader using pip:

uv pip install gs1grader

Or if you want to install from source:

# Clone the repo
git clone https://github.com/Ceyeborg/GS1Grader.git
cd GS1Grader

poetry install

Usage

Here's a simple example of how to use GS1Grader:

from gs1grader.grader_api import DataMatrixGradeAPI

# Create a grading API instance
grader_api = DataMatrixGradeAPI()

# Grade an image using the modulation grader
grade, explanation = grader_api.grade_datamatrix(
    image_path="path/to/your/datamatrix.png",
    grade_type="modulation",
    explanation_path="."
)

# Print the results
print(f"Grade: {grade}")
if explanation:
    print(f"Explanation: {explanation}")

Available Grading Methods

The library currently supports the following grading methods:

• modulation: Evaluates the modulation quality of the Data Matrix
• symbol_contrast: Evaluates the symbol contrast quality

API Reference

DataMatrixGradeAPI

The main class for grading Data Matrix codes.

Methods:

• grade_datamatrix(image_path: str, grade_type: str, explain: bool = False):
  • image_path: Path to the Data Matrix image file
  • grade_type: Type of grading to perform ("modulation" or "symbol_contrast")
  • explanation_path: Provide a path to save png of the detailed explanation of the grade (optional)
  • Returns: A tuple of (grade, explanation)

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0) - see the LICENSE file for details.

The AGPL-3.0 is a copyleft license that requires anyone who distributes your code or a derivative work to make the source available under the same terms, and also requires you to provide the source code to users who interact with your software as a service.