This release requires PyTorch >= v1.0.0 to function properly. Please install the latest version from https://github.com/pytorch/pytorch/releases Breaking Changes There are no breaking changes in this release. Bug Fixes NMS now screens out nan and inf values which caused it to hang during some edge cases. Added Functionality Rectangular Inference. detect.py now automatically processes images, videos and webcam feeds using rectangular inference, letterboxing to the minimum viable 32-multiple. This speeds up inference by up to 40% on HD video: https://github.com/ultralytics/yolov3/issues/232 Conv2d + Batchnorm2d Fusion: detect.py now automatically fuses the Conv2d and Batchnorm2d layes in the model before running inference. This speeds up inference by about 5-10%. https://github.com/ultralytics/yolov3/issues/224 Hyperparameters all parameterized and grouped togethor in train.py now. Genetic Hyperparameter Evolution code added to train.py. Performance https://cloud.google.com/deep-learning-vm/ Machine type: n1-standard-8 (8 vCPUs, 30 GB memory) CPU platform: Intel Skylake GPUs: K80 ($0.198/hr), P4 ($0.279/hr), T4 ($0.353/hr), P100 ($0.493/hr), V100 ($0.803/hr) HDD: 100 GB SSD Dataset: COCO train 2014 GPUs batch_size batch time epoch time epoch cost <i></i> (images) (s/batch) 1 K80 16 1.43s 175min $0.58 1 P4 8 0.51s 125min $0.58 1 T4 16 0.78s 94min $0.55 1 P100 16 0.39s 48min $0.39 2 P100 32 0.48s 29min $0.47 4 P100 64 0.65s 20min $0.65 1 V100 16 0.25s 31min $0.41 2 V100 32 0.29s 18min $0.48 4 V100 64 0.41s 13min $0.70 8 V100 128 0.49s 7min $0.80 TODO (help and PR's welcome!) Add iOS App inference to photos and videos in Camera Roll, as well as 'Flexible', or at least rectangular inference. https://github.com/ultralytics/yolov3/issues/224 Add parameter to switch between 'darknet' and 'power' wh methods. https://github.com/ultralytics/yolov3/issues/168 YAPF linting (including possible wrap to PEP8 79 character-line standard) https://github.com/ultralytics/yolov3/issues/88. Resolve mAP bug: https://github.com/ultralytics/yolov3/issues/222 Rectangular training. https://github.com/ultralytics/yolov3/issues/232 Genetic Hyperparameter Evolution. HELP NEEDED HERE. If you have available hardware please contact us, as we need help expanding our hyperparameter search, for the benefit of everyone!