Use Case and High-Level Description

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).


-> 菊池朋子


Metric Value
GFlops 117.136
MParams 15.31
Accuracy on Kondate test set and test set generated from Nakayosi 98.16%
Source framework PyTorch*

Accuracy Values

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.

Legal Information

[*] Other names and brands may be claimed as the property of others.