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Glenn Jocher 2019-11-30 14:16:01 -08:00
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@ -151,24 +151,24 @@ YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**YOLOv3-SPP ultralytics** |416 |16.0<br>
YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**YOLOv3-SPP ultralytics** |608 |16.6<br>33.0<br>37.0<br>**40.7** |35.5<br>57.9<br>60.6<br>**60.7** YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**YOLOv3-SPP ultralytics** |608 |16.6<br>33.0<br>37.0<br>**40.7** |35.5<br>57.9<br>60.6<br>**60.7**
```bash ```bash
$ python3 test.py --save-json --img-size 608 --nms-thres 0.65 --weights ultralytics68.pt Namespace(batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.001, data='data/coco.data', device='', img_size=608, iou_thres=0.5, nms_thres=0.7, save_json=True, weights='ultralytics68.pt')
Namespace(batch_size=16, cfg='cfg/yolov3-spp.cfg', conf_thres=0.001, data='data/coco.data', device='', img_size=608, iou_thres=0.5, nms_thres=0.65, save_json=True, weights='ultralytics68.pt') Using CUDA device0 _CudaDeviceProperties(name='Tesla P100-PCIE-16GB', total_memory=16280MB)
Using CUDA device0 _CudaDeviceProperties(name='Tesla T4', total_memory=15079MB)
Class Images Targets P R mAP@0.5 F1: 100% 313/313 [06:52<00:00, 1.24it/s] Downloading https://drive.google.com/uc?export=download&id=1Jm8kqnMdMGUUxGo8zMFZMJ0eaPwLkxSG as ultralytics68.pt... Done (2.2s)
all 5e+03 3.58e+04 0.107 0.779 0.59 0.182 Class Images Targets P R mAP@0.5 F1: 100% 313/313 [16:23<00:00, 1.59s/it]
Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.404 <--- all 5e+03 3.58e+04 0.0465 0.831 0.586 0.0868
Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.597 <--- Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.407
Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.438 Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.598
Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.241 Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.444
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.444 Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.245
Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.446
Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511 Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.511
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.326 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.326
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.533 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.537
Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.570 Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.595
Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.393 Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.427
Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.614 Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.641
Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.691 Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.706
``` ```
# Citation # Citation