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43.1mAP@0.5:0.95 on COCO2014

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@glenn-jocher glenn-jocher released this 04 May 19:24
· 399 commits to master since this release
5d42cc1

This release requires PyTorch >= v1.4 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

  • Various

Added Functionality

  • Improved training and test ground truth and prediction plotting. #1114
  • Increased augmentation speed. #1110
  • Improved Tensorboard integration.
  • Auto class hyperparameter update based on dataset class count.
  • Inference time augmentation option added now with --augment argument in test.py and detect.py.
  • Rectangular training with --rect argument in train.py

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 (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. #224