This release is a minor update implementing numerous bug fixes, feature additions and performance improvements from https://github.com/ultralytics/yolov5 to this repo. Models remain unchanged from v9.0 release. Branch Notice The ultralytics/yolov3 repository is now divided into two branches: Master branch: Forward-compatible with all YOLOv5 models and methods (recommended).$ git clone https://github.com/ultralytics/yolov3 # master branch (default) Archive branch: Backwards-compatible with original darknet *.cfg models (⚠️ no longer maintained). $ git clone -b archive https://github.com/ultralytics/yolov3 # archive branch <img src="https://user-images.githubusercontent.com/26833433/100382066-c8bc5200-301a-11eb-907b-799a0301595e.png" width="800"> ** GPU Speed measures end-to-end time per image averaged over 5000 COCO val2017 images using a V100 GPU with batch size 32, and includes image preprocessing, PyTorch FP16 inference, postprocessing and NMS. EfficientDet data from google/automl at batch size 8. Pretrained Checkpoints Model AP^val AP^test AP₅₀ Speed_GPU FPS_GPU params FLOPS YOLOv3 43.3 43.3 63.0 4.8ms 208 61.9M 156.4B YOLOv3-SPP 44.3 44.3 64.6 4.9ms 204 63.0M 157.0B YOLOv3-tiny 17.6 34.9 34.9 1.7ms 588 8.9M 13.3B AP^test denotes COCO test-dev2017 server results, all other AP results denote val2017 accuracy. All AP numbers are for single-model single-scale without ensemble or TTA. Reproduce mAP by python test.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65 Speed_GPU averaged over 5000 COCO val2017 images using a GCP n1-standard-16 V100 instance, and includes image preprocessing, FP16 inference, postprocessing and NMS. NMS is 1-2ms/img. Reproduce speed by python test.py --data coco.yaml --img 640 --conf 0.25 --iou 0.45 All checkpoints are trained to 300 epochs with default settings and hyperparameters (no autoaugmentation). Test Time Augmentation (TTA) runs at 3 image sizes. Reproduce TTA** by python test.py --data coco.yaml --img 832 --iou 0.65 --augment Requirements Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run: $ pip install -r requirements.txt