YOLOv3 Files

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 time	epoch cost
K80	1	32 x 2	11	175 min	$0.41
T4	1 2	32 x 2 64 x 1	41 61	48 min 32 min	$0.09 $0.11
V100	1 2	32 x 2 64 x 1	122 178	16 min 11 min	$0.21 $0.28
2080Ti	1 2	32 x 2 64 x 1	81 140	24 min 14 min	- -

mAP

	Size	COCO mAP @0.5...0.95	COCO mAP @0.5
YOLOv3-tiny YOLOv3 YOLOv3-SPP YOLOv3-SPP-ultralytics	320	14.0 28.7 30.5 37.7	29.1 51.8 52.3 56.8
YOLOv3-tiny YOLOv3 YOLOv3-SPP YOLOv3-SPP-ultralytics	416	16.0 31.2 33.9 41.2	33.0 55.4 56.9 60.6
YOLOv3-tiny YOLOv3 YOLOv3-SPP YOLOv3-SPP-ultralytics	512	16.6 32.7 35.6 42.6	34.9 57.7 59.5 62.4
YOLOv3-tiny YOLOv3 YOLOv3-SPP YOLOv3-SPP-ultralytics	608	16.6 33.1 37.0 43.1	35.4 58.2 60.7 62.8

TODO

• NA