pytorch yolov5运行日志

 

wind_2021) F:\PytorchProject\Yolov5_DeepSort_Pytorch-master\yolov5>
(wind_2021) F:\PytorchProject\Yolov5_DeepSort_Pytorch-master\yolov5>python detect.py --weights yolov5s.pt
detect: weights=['yolov5s.pt'], source=data\images, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=runs\detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False
YOLOv5  2021-10-12 torch 1.8.1+cu111 CUDA:0 (NVIDIA GeForce RTX 3080 Laptop GPU, 16384.0MB)

Fusing layers...
Model Summary: 224 layers, 7266973 parameters, 0 gradients
image 1/2 F:\PytorchProject\Yolov5_DeepSort_Pytorch-master\yolov5\data\images\bus.jpg: 640x480 4 persons, 1 bus, Done. (0.016s)
image 2/2 F:\PytorchProject\Yolov5_DeepSort_Pytorch-master\yolov5\data\images\zidane.jpg: 384x640 2 persons, 1 tie, Done. (0.020s)
Speed: 1.0ms pre-process, 17.9ms inference, 7.0ms NMS per image at shape (1, 3, 640, 640)
Results saved to runs\detect\exp

(wind_2021) F:\PytorchProject\Yolov5_DeepSort_Pytorch-master\yolov5>
(wind_2021) F:\PytorchProject\Yolov5_DeepSort_Pytorch-master\yolov5>

 

 

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