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使用YOLO_v3_tiny和B-CNN实现街头车辆的检测和车辆属性的多标签识别 Using yolo_v3_tiny to do vehicle or car detection and attribute's multilabel classification or recognize

Results 34 Vehicle-Car-detection-and-multilabel-classification issues
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Thank you very much for your outstanding contribution. I have a question. What are the requirements of this network for inputting pictures? Why do I input other pictures and report...

将RepNet-MDNet-VehicleReID项目中的模型下载下来,用在此项目中,出现报错。 => device: cuda:0 => ./car_540000.weights loaded. => car detection model initiated. Traceback (most recent call last): File "VehicleDC.py", line 385, in DR_model = Car_DC(src_dir=args.src_dir, dst_dir=args.dst_dir) File "VehicleDC.py", line 246,...

hello,could you please supply requirements.txt file in your project?

The output topK's K is fixed now. Do you think training a classifier to predict the value of K for every input is a good solution? Thank you very much.

作者可以添加一个对视频进行识别的函数吗?谢谢!

作者好,我在1080和1660ti的机器上跑你的程序,目标检测的速度和识别的速度都达不到你描述的10ms、18ms的速度,请问还有什么技巧吗?希望尽快回复,谢谢

请问在您的测试数据集上准确识别率有多少

你好,我看你在多标签分类中用到了B-CNN,在VehicleDC.py中这样写的: “X = torch.bmm(X, torch.transpose(X, 1, 2)) / (1 ** 2) # Bi-linear CNN” 我看了B-CNN的代码,并没有看到这样的方法。 请问你这样做的根据和目的是什么? 也可能是我看漏掉了,还请作者指点。非常感谢

@CaptainEven , 谢谢你的分享,我现在有个疑问,最后一层FC出来的结果为什么没有归一化到(0,1)之间。你能帮忙解答一下吗?