DataXujing/YOLO-v5
A PyTorch YOLOv5 tutorial for training object detection models on custom datasets in medical endoscopy.
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This repository provides a detailed guide for training YOLOv5 on custom datasets using PyTorch, with a specific focus on medical endoscopy object detection applications. It covers environment setup, dataset preparation, configuration files, and the training process. The project also references TensorRT acceleration for model inference.
Frequently asked
- What is DataXujing/YOLO-v5?
- A PyTorch YOLOv5 tutorial for training object detection models on custom datasets in medical endoscopy.
- Is YOLO-v5 open source?
- Yes — DataXujing/YOLO-v5 is open source, released under the GPL-3.0 license.
- What language is YOLO-v5 written in?
- DataXujing/YOLO-v5 is primarily written in Jupyter Notebook.
- How popular is YOLO-v5?
- DataXujing/YOLO-v5 has 973 stars on GitHub.
- Where can I find YOLO-v5?
- DataXujing/YOLO-v5 is on GitHub at https://github.com/DataXujing/YOLO-v5.