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基于Yolov5车牌检测,更快更准.

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想请问下数据集在哪里呀,可不可以分享一下voc格式的呢,感谢!

建议增加requirements.txt文件 方面查看依赖

Traceback (most recent call last): File "D:/Project/Pycharm/License-Plate-Detector-master/detect_plate.py", line 162, in f = show_files("/home/zeusee/plate/", []) File "D:/Project/Pycharm/License-Plate-Detector-master/detect_plate.py", line 145, in show_files file_list = os.listdir(path) FileNotFoundError: [WinError 3] 系统找不到指定的路径。: '/home/zeusee/plate/'

![image](https://user-images.githubusercontent.com/76094318/159122999-fa181079-5cf1-4e93-9a70-bd6f9eb5ba93.png)

这个模型不是多分类的吗?能否训练一个车牌多分类的模型,包括蓝牌,大使馆牌,警牌等

请问这个车牌检测模型在CCPD上的AP值能到多少呢

1、源程序build完直接运行报错如下: ![image](https://user-images.githubusercontent.com/70998835/154208813-5d723118-94b5-4b62-86d7-1db7f52dc1b9.png) 2、修改了文件路径后运行报错如下: ```text D:\InstallationDir\anaconda\python.exe E:/lxx/workProjects/uniappHyperLPR/License-Plate-Detector/detect_plate.py Namespace(weights='runs/train/exp/weights/last.pt', image='data/images/test.jpg', img_size=640) Traceback (most recent call last): File "D:\InstallationDir\anaconda\lib\site-packages\urllib3\connectionpool.py", line 700, in urlopen self._prepare_proxy(conn) File "D:\InstallationDir\anaconda\lib\site-packages\urllib3\connectionpool.py", line 994, in _prepare_proxy conn.connect() File "D:\InstallationDir\anaconda\lib\site-packages\urllib3\connection.py",...

可以留一个联系方式马?或是邦确认一下,detect_plate.py model and test data 现在是否可以执行,谢谢

求教作者,想要目前模型在cpu上实现30fps的推理速度,有没有什么方法?感谢!