mAP updates
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README.md
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README.md
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@ -140,10 +140,10 @@ Success: converted 'weights/yolov3-spp.pt' to 'converted.weights'
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<i></i> |Size |COCO mAP<br>@0.5...0.95 |COCO mAP<br>@0.5
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<i></i> |Size |COCO mAP<br>@0.5...0.95 |COCO mAP<br>@0.5
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--- | --- | --- | ---
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--- | --- | --- | ---
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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**
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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**
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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**
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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**
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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**
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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**
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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**
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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**
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- mAP@0.5 run at `--iou-thr 0.5`, mAP@0.5...0.95 run at `--iou-thr 0.7`
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- mAP@0.5 run at `--iou-thr 0.5`, mAP@0.5...0.95 run at `--iou-thr 0.7`
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- Darknet results: https://arxiv.org/abs/1804.02767
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- Darknet results: https://arxiv.org/abs/1804.02767
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@ -155,20 +155,20 @@ Namespace(augment=True, batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.00
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Using CUDA device0 _CudaDeviceProperties(name='Tesla V100-SXM2-16GB', total_memory=16130MB)
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Using CUDA device0 _CudaDeviceProperties(name='Tesla V100-SXM2-16GB', total_memory=16130MB)
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Class Images Targets P R mAP@0.5 F1: 100%|█████████| 313/313 [03:00<00:00, 1.74it/s]
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Class Images Targets P R mAP@0.5 F1: 100%|█████████| 313/313 [03:00<00:00, 1.74it/s]
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all 5e+03 3.51e+04 0.372 0.743 0.636 0.49
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all 5e+03 3.51e+04 0.373 0.744 0.637 0.491
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Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.450
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Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.454
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.643
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.644
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.486
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.497
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Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.265
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Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.270
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Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.498
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Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.504
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Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.577
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Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.577
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.361
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.363
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.593
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.599
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.654
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Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.668
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Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.486
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Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.502
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Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.701
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Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.724
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Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.804
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Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.805
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Speed: 21.3/3.0/24.4 ms inference/NMS/total per 640x640 image at batch-size 16
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Speed: 21.3/3.0/24.4 ms inference/NMS/total per 640x640 image at batch-size 16
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```
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```
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