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Semantic Segmentation Processor

Image Semantic Segmentation based on the state-of-art DeepLab Tensorflow model.

The Semantic Segmentation is the process of associating each pixel of an image with a class label, (such as flower, person, road, sky, ocean, or car). Unlike the Instance Segmentation, which produces instance-aware region masks, the Semantic Segmentation produces class-aware masks. For implementing Instance Segmentation consult the Object Detection Service instead.

The Semantic Segmentation Processor uses the Semantic Segmentation Function library and the TensorFlow Service.

Payload

The incoming type is byte[], and the content type is application/octet-stream. The processor processes the input byte[] image and outputs augmented byte[] image payload and json header.

Processor’s input is an image byte array, and the output is an augmented image byte array, and a JSON header semantic_segmentation in this format:

[
    [ 0, 0, 0 ],
    [ 127, 127, 127 ],
    [ 255, 255, 255 ]
    ...
]

The output header json format represents the color pixel map computed from the input image.

Options

semantic.segmentation.color-map-uri

Every pre-trained model is based on certain object color maps. The pre-defined options are: - classpath:/colormap/citymap_colormap.json - classpath:/colormap/ade20k_colormap.json - classpath:/colormap/black_white_colormap.json - classpath:/colormap/mapillary_colormap.json (String, default: classpath:/colormap/citymap_colormap.json)

semantic.segmentation.debug-output

save output image inn the local debugOutputPath path. (Boolean, default: false)

semantic.segmentation.debug-output-path

<documentation missing> (String, default: semantic-segmentation-result.png)

semantic.segmentation.mask-transparency

The alpha color of the computed segmentation mask image. (Float, default: 0.45)

semantic.segmentation.model

pre-trained tensorflow semantic segmentation model. (String, default: https://download.tensorflow.org/models/deeplabv3_mnv2_cityscapes_train_2018_02_05.tar.gz#frozen_inference_graph.pb)

semantic.segmentation.output-type

Specifies the output image type. You can return either the input image with the computed mask overlay, or the mask alone. (OutputType, default: <none>, possible values: blended,mask)