This project focuses on the identification of vehicles in images using OpenCV and the YOLOv5 model. Driven by my interest in computer vision and deep learning, I developed this project to deepen my understanding of OpenCV's capabilities.
The YOLOv5 model was trained on a dataset comprising 2,704 images of vehicles captured in traffic scenarios. The model is designed to detect a variety of vehicle types, including:
- Ambulance
- Army Vehicle
- Auto Rickshaw
- Bicycle
- Bus
- Car
- Garbage Van
- Human Hauler
- Minibus
- Minivan
- Motorbike
- Pickup
- Police Car
- Rickshaw
- Scooter
- SUV
- Taxi
- Three Wheelers (CNG)
- Truck
- Van
- Wheelbarrow
The training dataset can be accessed via the following link: Kaggle Dataset
A validation set of images and corresponding labels has been included in this repository to ensure the accuracy and reliability of the model.
Model is trained for 50 epoches in colab, results of weights and configurations are attached in the repo
- Model trained using Google Colab Google Colab Notebook link