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car-object-detection

πŸš— Car Detection Using YOLOv5u (Ultralytics)

A simple, lightweight pipeline to detect cars using YOLOv5u on Google Colab. This repo contains code for training, evaluating, and testing YOLO models on a custom dataset.


πŸ“Œ Features

  • πŸ” Real-time object detection (car detection)
  • 🧠 Finetuned YOLOv5u on custom dataset
  • ☁️ Runs fully on Google Colab (no local setup needed)
  • πŸ“Š Easy evaluation and result visualization

πŸ§ͺ Demo

Demo GIF or Screenshot


πŸ“ Directory Structure

.
β”œβ”€β”€ data/
β”‚   └── car.yaml           # Dataset configuration
β”œβ”€β”€ images/
β”‚   β”œβ”€β”€ training_images/   # Training images
β”‚   └── testing_images/    # Test images
β”œβ”€β”€ labels/
β”‚   β”œβ”€β”€ training_images/   # YOLO-format .txt labels
β”‚   └── testing_images/    # YOLO-format .txt labels (optional)
β”œβ”€β”€ runs/
β”‚   └── car_detect/        # Output model weights and logs
└── car_detection.ipynb    # Google Colab Notebook

About

πŸš— Car Detection Using YOLOv5u on Google Colab A complete pipeline for training, evaluating, and testing a YOLOv5u (Ultralytics) object detection model on a custom car dataset. This project runs entirely in Google Colab and includes dataset setup, training scripts, model evaluation, and image inference. Designed for ease of use and fast prototyping

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