senlinuc / caffe_ocr

主流ocr算法研究实验性的项目,目前实现了CNN+BLSTM+CTC架构
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Accuracy Drop on Inception and DenseNet #37

Open huangpanxx opened 6 years ago

huangpanxx commented 6 years ago

Hi senlinuc,

Thanks for your kindly sharing:). I noticed that you've tried many improvements based on standard crnn. But there is a significant accuracy drop(especially no lexicon case) with more powerful cnn structures such as inception net and densenet. Do you have some analysis on this? Is it caused by parameter reduction or some thing else? It will be great if you could share your configs for mjsynth experiments. I'm very curious about the 3 models' cnn settings.

Thanks.

网格结构 predict-CPU predict-GPU 准确率-no lexicon 准确率-lexicon-minctcloss 模型大小
crnn 67.13ms 10.28ms 0.8435 0.9163 32MB
inception-bn-res-blstm 41.62ms 8.68ms 0.7353 0.8609 15MB
densenet-res-blstm N/A 6.07ms 0.7548 0.893 11MB