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[ECCV 2018] CCPD: a diverse and well-annotated dataset for license plate detection and recognition

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Why does the test fail to display Chinese character but have english and number license plates?

Hey, So first of all i'm not interested in the recognition but just detection/localizatoin of the plate and i tried images of an independent dataset and demo.py failed badly as...

In order to compare the performance in the paper, can you elaborate on the image list of the 100k training set?

不能做一张图片中有多车牌的检测和识别 对于没有车牌的图片也会输出检测结果 检测部分不支持旋转检测 识别部分不支持不定长字符的识别(新能源车8位);使用了7个不同的分类器,模型参数多。

Thank you for your excellent work.and there i have one question.When it comes to character recognition, you use seven different classifiers, and the next five categories should be the same....

皖开头的车牌占了训练集和测试集总数的90%以上,所以导致汉字识别能力较差。谁能共享下其他的训练集啊,谢谢。

Excuse me, it seems that the eval.py you provide only measures the recognition precision. Or maybe I just miss the code when reading your code? Can you provide a code...

First at all,thanks for your kindly open CCPD source and datasets,it is a great work. I had downloaded the dataset from the provide link, but, I found that the provide...

loss += 0.8 * nn.L1Loss().cuda()(fps_pred[:][:2], y[:][:2]) loss += 0.2 * nn.L1Loss().cuda()(fps_pred[:][2:], y[:][2:]) With reference to above lines? I understand you are taking .8 times loss of first two examples ??...

trainset: 100k images in ccpd_base folder testset: 20k images in ccpd_base folder from the 10th epoch to 100th epoch, the test accurate is Lingering around 95% Had I known what...