From 8d788e10c43066921ad92082520d086f82502dc6 Mon Sep 17 00:00:00 2001 From: Glenn Jocher Date: Tue, 31 Mar 2020 19:07:41 -0700 Subject: [PATCH] mAP updates --- README.md | 32 ++++++++++++++++---------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/README.md b/README.md index 7bbcbf86..2444700d 100755 --- a/README.md +++ b/README.md @@ -140,10 +140,10 @@ Success: converted 'weights/yolov3-spp.pt' to 'converted.weights' |Size |COCO mAP
@0.5...0.95 |COCO mAP
@0.5 --- | --- | --- | --- -YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0
28.7
30.5
**37.5** |29.1
51.8
52.3
**56.8** -YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**41.1** |33.0
55.4
56.9
**60.6** -YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**42.6** |34.9
57.7
59.5
**62.3** -YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**42.8** |35.4
58.2
60.7
**62.5** +YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0
28.7
30.5
**37.6** |29.1
51.8
52.3
**56.8** +YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0
31.2
33.9
**41.1** |33.0
55.4
56.9
**60.7** +YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6
32.7
35.6
**42.7** |34.9
57.7
59.5
**62.6** +YOLOv3-tiny
YOLOv3
YOLOv3-SPP
**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6
33.1
37.0
**42.9** |35.4
58.2
60.7
**62.6** - mAP@0.5 run at `--iou-thr 0.5`, mAP@0.5...0.95 run at `--iou-thr 0.7` - Darknet results: https://arxiv.org/abs/1804.02767 @@ -155,20 +155,20 @@ Namespace(augment=True, batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.00 Using CUDA device0 _CudaDeviceProperties(name='Tesla V100-SXM2-16GB', total_memory=16130MB) Class Images Targets P R mAP@0.5 F1: 100%|█████████| 313/313 [03:00<00:00, 1.74it/s] - all 5e+03 3.51e+04 0.372 0.743 0.636 0.49 + all 5e+03 3.51e+04 0.373 0.744 0.637 0.491 - Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.450 - Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.643 - Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.486 - Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.265 - Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.498 + Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.454 + Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.644 + Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.497 + Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.270 + Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.504 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.577 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.361 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.593 - Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.654 - Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.486 - Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.701 - Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.804 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.363 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599 + Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.668 + Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.502 + Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.724 + Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.805 Speed: 21.3/3.0/24.4 ms inference/NMS/total per 640x640 image at batch-size 16 ```