yolov5

Why we included this project

YOLOv5 is a PyTorch model for object detection that has been around long enough to become a dependable default in the computer vision field. The repository includes a complete training pipeline, so you can fine-tune a pretrained checkpoint on your own labeled data rather than building detection logic from scratch. Export paths to ONNX, TensorRT, CoreML, and TFLite make it straightforward to move a trained model to edge devices, mobile apps, or a production inference server. It is also a reasonable place to start if you are new to the field: the code is readable, the documentation is solid, and the volume of tutorials and community discussion means you will rarely be stuck for long. Teams that just need a working object-detection baseline will find the pretrained weights and documented workflows save most of the setup time.