This is the final release of the darknet-compatible version of the https://github.com/ultralytics/yolov3 repository. This release is backwards-compatible with darknet *.cfg files for model configuration. All pytorch (.pt) and darknet (.weights) models/backbones available are attached to this release in the Assets section below. Breaking Changes There are no breaking changes in this release. Bug Fixes Various Added Functionality Various Speed https://cloud.google.com/deep-learning-vm/ Machine type: preemptible n1-standard-8 (8 vCPUs, 30 GB memory) CPU platform: Intel Skylake GPUs: K80 ($0.14/hr), T4 ($0.11/hr), V100 ($0.74/hr) CUDA with Nvidia Apex FP16/32 HDD: 300 GB SSD Dataset: COCO train 2014 (117,263 images) Model: yolov3-spp.cfg Command: python3 train.py --data coco2017.data --img 416 --batch 32 GPU n --batch-size img/s epoch<br>time epoch<br>cost K80 1 32 x 2 11 175 min $0.41 T4 1<br>2 32 x 2<br>64 x 1 41<br>61 48 min<br>32 min $0.09<br>$0.11 V100 1<br>2 32 x 2<br>64 x 1 122<br>178 16 min<br>11 min $0.21<br>$0.28 2080Ti 1<br>2 32 x 2<br>64 x 1 81<br>140 24 min<br>14 min -<br>- mAP <i></i> Size COCO mAP<br>@0.5...0.95 COCO mAP<br>@0.5 YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>YOLOv3-SPP-ultralytics 320 14.0<br>28.7<br>30.5<br>37.7 29.1<br>51.8<br>52.3<br>56.8 YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>YOLOv3-SPP-ultralytics 416 16.0<br>31.2<br>33.9<br>41.2 33.0<br>55.4<br>56.9<br>60.6 YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>YOLOv3-SPP-ultralytics 512 16.6<br>32.7<br>35.6<br>42.6 34.9<br>57.7<br>59.5<br>62.4 YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>YOLOv3-SPP-ultralytics 608 16.6<br>33.1<br>37.0<br>43.1 35.4<br>58.2<br>60.7<br>62.8 TODO NA