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Dog Detection using YOLOv5

Description

This repository is part of a project that I worked on with https://github.com/Better1337 as part of the Artificial Intelligence Techniques(Metody Sztucznej Inteligencji) course. We used https://github.com/ultralytics/yolov5 and the dataset from http://vision.stanford.edu/aditya86/ImageNetDogs/

Requirements

  • Python 3.x
  • PyTorch
  • OpenCV
  • Pillow
  • NumPy

Data

The training model utilizes a set of labeled images, available from the following dataset: Stanford Dogs Dataset. Ensure your dataset is configured correctly for YOLOv5. The parameters used to train the model(best.pt) can be found at the begginning of the CamDetection.py

  • Dataset Setup: Annotations must adhere to YOLOv5's requirements, formatted as .txt files containing class_index x_center y_center width height. For comprehensive guidance on preparing your data, visit YOLOv5's guide to Training on Custom Data.

About

Real-time dog detection on images, videos and video streams with YOLOv5 and Python.

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