ultralytics/yolov3: v8

#ultralytics/yolov3: v8| 来源: 网络整理| 查看: 265

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 epochtime epochcost K80 1 32 x 2 11 175 min $0.41 T4 12 32 x 264 x 1 4161 48 min32 min $0.09$0.11 V100 12 32 x 264 x 1 122178 16 min11 min $0.21$0.28 2080Ti 12 32 x 264 x 1 81140 24 min14 min -- mAP Size COCO [email protected] COCO [email protected] YOLOv3-tinyYOLOv3YOLOv3-SPPYOLOv3-SPP-ultralytics 320 14.028.730.537.7 29.151.852.356.8 YOLOv3-tinyYOLOv3YOLOv3-SPPYOLOv3-SPP-ultralytics 416 16.031.233.941.2 33.055.456.960.6 YOLOv3-tinyYOLOv3YOLOv3-SPPYOLOv3-SPP-ultralytics 512 16.632.735.642.6 34.957.759.562.4 YOLOv3-tinyYOLOv3YOLOv3-SPPYOLOv3-SPP-ultralytics 608 16.633.137.043.1 35.458.260.762.8 TODO NA

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