CCPD
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[ECCV 2018] CCPD: a diverse and well-annotated dataset for license plate detection and recognition
论抠图的方法
请问向two-stage网络的抠图也是和这个的解决办法一样吗,作者可以参考一下他们的实现方法
in forward(self, x) 191 # input = Variable(torch.rand(2, 1, 10, 10), requires_grad=True) 192 # rois = Variable(torch.LongTensor([[0, 1, 2, 7, 8], [0, 3, 3, 8, 8], [1, 3, 3, 8,...
iname = img_name.rsplit('/', 1)[-1].rsplit('.', 1)[0].split('-') [leftUp, rightDown] = [[int(eel) for eel in el.split('&')] for el in iname[2].split('_')] ori_w, ori_h = float(img.shape[1]), float(img.shape[0]) 这么获取[leftUp, rightDown] 以及ori_w, ori_h ,是正确的吗? 我怎么觉得这样扣下来的车牌图会不完整啊?!
Can I test code for Vehicle Identification Number(VIN) number recognition.
line376: loss += 0.8 * nn.L1Loss().cuda()(fps_pred[:][:2], y[:][:2]) line377: loss += 0.2 * nn.L1Loss().cuda()(fps_pred[:][2:], y[:][2:]) In the file rpnet.py ,we can know that these two lines refers the L1Loss about the...
cpu
I am about to run the demo.py. If I only use **cpu**, how should I modify the code?
文件名称解析说明,没有详细对应例子,虽然说了包含的内容,但没有给出对应关系,麻烦提供一下解析代码
i run the demo.py with my own license plate images with different jpeg distortion level .but the accuaracy is extremely low . Is there something wrong ?
should the image size always be (480,480) in the demo.py?
I tested on the new data set, the accuracy is very low, but after training, the accuracy is high; I think the generalization ability of the model is very poor......