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@ -155,11 +155,11 @@ YOLOv3-tiny<br>YOLOv3<br>YOLOv3-SPP<br>**[YOLOv3-SPP-ultralytics](https://drive.
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```bash
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```bash
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$ python3 test.py --cfg yolov3-spp.cfg --weights yolov3-spp-ultralytics.pt --img 608
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$ python3 test.py --cfg yolov3-spp.cfg --weights yolov3-spp-ultralytics.pt --img 608
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Namespace(batch_size=32, cfg='yolov3-spp', conf_thres=0.001, data='data/coco2014.data', device='', img_size=608, iou_thres=0.6, save_json=True, single_cls=False, task='test', weights='last82.pt')
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Namespace(batch_size=32, cfg='cfg/yolov3-spp.cfg', conf_thres=0.001, data='data/coco2014.data', device='', img_size=608, iou_thres=0.6, save_json=True, single_cls=False, task='test', weights='weights/yolov3-spp-ultralytics.pt')
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Using CUDA device0 _CudaDeviceProperties(name='Tesla P100-PCIE-16GB', total_memory=16280MB)
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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% 157/157 [03:12<00:00, 1.50it/s]
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Class Images Targets P R mAP@0.5 F1: 100%|█████| 157/157 [02:46<00:00, 1.06s/it]
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all 5e+03 3.51e+04 0.0573 0.871 0.611 0.106
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all 5e+03 3.51e+04 0.822 0.433 0.611 0.551
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Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.419
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Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.419
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.618
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Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.618
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.448
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Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.448
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