This is a network for handwritten japanese text recognition scenario. It consists of VGG16-like backbone, reshape layer and a fully connected layer. The network is able to recognize japanese text (characters in datasets Kondate and Nakayosi).
|Accuracy on Kondate test set and test set generated from Nakayosi||98.16%|
This demo adopts label error rate as the metric for accuracy.
Shape: [1x1x96x2000] - An input image in the format [BxCxHxW], where:
Note that the source image should be converted to grayscale, resized to spefic height (such as 96) while keeping aspect ratio, normalized to [-1, 1] and right bottom padded
The net outputs a blob with the shape [186, 1, 1161] in the format [WxBxL], where:
The network output can be decoded by CTC Greedy Decoder.
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