This is a network for text recognition scenario. It consists of VGG16-like backbone and bidirectional LSTM encoder-decoder. The network is able to recognize case-insensitive alpha-numeric text (36 unique symbols).
-> openvino
| Metric | Value |
|---|---|
| Accuracy on the alphanumeric subset of ICDAR13 | 0.8818 |
| Text location requirements | Tight aligned crop |
| GFlops | 1.485 |
| MParams | 5.568 |
| Source framework | TensorFlow |
Shape: [1x1x32x120] - An input image in the format [BxCxHxW], where:
- B - batch size
- C - number of channels
- H - image height
- W - image width
Note that the source image should be tight aligned crop with detected text converted to grayscale.
The net outputs a blob with the shape [30, 1, 37] in the format [WxBxL], where:
- W - output sequence length
- B - batch size
- L - confidence distribution across alpha-numeric symbols: "0123456789abcdefghijklmnopqrstuvwxyz#", where # - special blank character for CTC decoding algorithm.
The network output can be decoded by CTC Greedy Decoder or CTC Beam Search decoder.
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