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text-recognition-resnet-fc

Use-case and high-level description

text-recognition-resnet-fc is a simple and preformant scene text recognition model based on ResNet with Fully Connected text recognition head. Source implementation on a PyTorch* framework could be found here. Model is able to recognize alphanumeric text.

Specification

Metric

Value

Type

Scene Text Recognition

GFLOPs

40.3704

MParams

177.9668

Source framework

PyTorch*

Accuracy

Alphanumeric subset of common scene text recognition benchmarks are used. For your convenience you can see dataset size. Note, that we use here ICDAR15 alphanumeric subset without irregular (arbitrary oriented, perspective or curved) texts. See details here, section 4.1. All reported results are achieved without using any lexicon.

Dataset

Accuracy

Dataset size

ICDAR-03

92.96%

867

ICDAR-13

90.44%

1015

ICDAR-15

77.58%

1811

SVT

88.56%

647

IIIT5K

88.83%

3000

Input

Image, name: input, shape: 1, 1, 32, 100 in the format B, C, H, W, 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. Mean values: [127.5, 127.5, 127.5], scale factor for each channel: 127.5.

Outputs

Output tensor, name: output, shape: 1, 26, 37 in the format B, W, L, where:

  • W - output sequence length

  • B - batch size

  • L - confidence distribution across alphanumeric symbols: [s]0123456789abcdefghijklmnopqrstuvwxyz, where [s] - special end of sequence character for decoder.

The network output decoding process is pretty easy: get the argmax on L dimension, transform indices to letters and slice the resulting phrase on the first entry of end-of-sequence symbol.

Use text-detection demo

Model is supported by text-detection c++ demo(<omz_dir>/demos/text_detection_demo/cpp/main.cpp). In order to use this model in the demo, user should pass the following options:

  -tr_pt_first
  -dt "simple"

For more information, please, see documentation of the demo.

Demo usage

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:

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