How to Train YOLOv5 on a Custom Dataset

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YOLOv5 is the latest evolution in the YOLO family of object detection models. It's the first YOLO implementation native to PyTorch (rather than Darknet) and emphasizes ease of use and quickness of training and inference.  This YOLOv5 tutorial shows you how to train the model on your own dataset in Python.

Tools:
Roboflow - https://roboflow.com
Public datasets - https://public.roboflow.com
Colab notebook  - https://models.roboflow.com/object-de...
GitHub repo (for additional details, e.g. passing a video file or webcam for inference): https://github.com/ultralytics/yolov5

YOLOv5 Details:
YOLOv4 vs YOLOv5 - https://blog.roboflow.com/yolov4-vers...
How to Train YOLOv5 (blog) - https://blog.roboflow.com/how-to-trai...

Labeling guides for creating bounding boxes:
CVAT - https://blog.roboflow.com/getting-sta...
LabelImg - https://blog.roboflow.com/getting-sta...

Explore popular templates to kickstart your project:
https://roboflow.com/templates

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