text-detection-0004

Use Case and High-Level Description

Text detector based on PixelLink architecture with MobileNetV2, depth_multiplier=1.4 as a backbone for indoor/outdoor scenes.

Example

_images/text-detection-0004.png

Specification

Metric

Value

F-measure (Harmonic mean of precision and recall on ICDAR2015)

79.43%

GFlops

23.305

MParams

4.328

Source framework

TensorFlow*

Inputs

Image, name: input, shape: 1, 3, 768, 1280 in the format B, C, H, W, where:

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order: BGR.

Outputs

  1. name: model/link\_logits\_/add, shape: 1, 16, 192, 320 - logits related to linkage between pixels and their neighbors.

  2. name: model/segm\_logits/add, shape: 1, 2, 192, 320 - logits related to text/no-text classification for each pixel.

Refer to PixelLink and demos for details.

Use Case and High-Level Description

Text detector based on PixelLink architecture with MobileNetV2, depth_multiplier=1.4 as a backbone for indoor/outdoor scenes.

Example

_images/text-detection-0004.png

Specification

Metric

Value

F-measure (Harmonic mean of precision and recall on ICDAR2015)

79.43%

GFlops

23.305

MParams

4.328

Source framework

TensorFlow*

Inputs

Image, name: input, shape: 1, 3, 768, 1280 in the format B, C, H, W, where:

  • B - batch size

  • C - number of channels

  • H - image height

  • W - image width

Expected color order: BGR.

Outputs

  1. name: model/link\_logits\_/add, shape: 1, 16, 192, 320 - logits related to linkage between pixels and their neighbors.

  2. name: model/segm\_logits/add, shape: 1, 2, 192, 320 - logits related to text/no-text classification for each pixel.

Refer to PixelLink and demos for details.

Legal Information

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