mAP updates

This commit is contained in:
Glenn Jocher 2020-03-31 19:07:41 -07:00
parent 02802e67f2
commit 8d788e10c4
1 changed files with 16 additions and 16 deletions

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@ -140,10 +140,10 @@ Success: converted 'weights/yolov3-spp.pt' to 'converted.weights'
<i></i> |Size |COCO mAP<br>@0.5...0.95 |COCO mAP<br>@0.5 <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](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0<br>28.7<br>30.5<br>**37.5** |29.1<br>51.8<br>52.3<br>**56.8** YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |320 |14.0<br>28.7<br>30.5<br>**37.6** |29.1<br>51.8<br>52.3<br>**56.8**
YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0<br>31.2<br>33.9<br>**41.1** |33.0<br>55.4<br>56.9<br>**60.6** YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |416 |16.0<br>31.2<br>33.9<br>**41.1** |33.0<br>55.4<br>56.9<br>**60.7**
YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6<br>32.7<br>35.6<br>**42.6** |34.9<br>57.7<br>59.5<br>**62.3** YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |512 |16.6<br>32.7<br>35.6<br>**42.7** |34.9<br>57.7<br>59.5<br>**62.6**
YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6<br>33.1<br>37.0<br>**42.8** |35.4<br>58.2<br>60.7<br>**62.5** YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.google.com/open?id=1UcR-zVoMs7DH5dj3N1bswkiQTA4dmKF4)** |608 |16.6<br>33.1<br>37.0<br>**42.9** |35.4<br>58.2<br>60.7<br>**62.6**
- mAP@0.5 run at `--iou-thr 0.5`, mAP@0.5...0.95 run at `--iou-thr 0.7` - 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 - 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) 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] 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=0.50:0.95 | area= all | maxDets=100 ] = 0.454
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.643 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.644
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.486 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.497
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.265 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 ] = 0.498 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 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= 1 ] = 0.363
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= 10 ] = 0.599
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.654 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 ] = 0.486 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 ] = 0.701 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 ] = 0.804 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 Speed: 21.3/3.0/24.4 ms inference/NMS/total per 640x640 image at batch-size 16
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