Releasing a New YOLOv3 Implementation in PyTorch

Roboflow has introduced support for a PyTorch implementation of the YOLOv3 model, originally developed by Ultralytics, in response to user requests, offering improved performance over their previous Keras version. This new implementation showed notable results in initial tests, achieving over 0.93 recall and 0.978 mAP@50 on a challenging chess piece identification task after 300 epochs on Google Colab. Existing Roboflow users can easily train a model using this PyTorch implementation by exporting their dataset with "YOLO Darknet Weights" and inserting the generated code into the provided PyTorch notebook. Roboflow offers a free service for small datasets, providing a user-friendly environment for those new to the platform, with a comprehensive onboarding tutorial available to guide new users.