Converting an ONNX Mask R-CNN Model

The instructions below are applicable only to the Mask R-CNN model converted to the ONNX file format from the maskrcnn-benchmark model.

  1. Download the pretrained model file from onnx/models :

    • commit-SHA: 8883e49e68de7b43e263d56b9ed156dfa1e03117.

  2. Generate the Intermediate Representation of the model by changing your current working directory to the Model Optimizer installation directory and running Model Optimizer with the following parameters:

     mo \
    --input_model mask_rcnn_R_50_FPN_1x.onnx \
    --input "0:2" \
    --input_shape [1,3,800,800] \
    --mean_values [102.9801,115.9465,122.7717] \
    --transformations_config front/onnx/mask_rcnn.json

Be aware that the height and width specified with the input_shape command line parameter could be different. For more information about supported input image dimensions and required pre- and post-processing steps, refer to the documentation.

  1. Interpret the outputs of the generated IR file: masks, class indices, probabilities and box coordinates.

    • masks.

    • class indices.

    • probabilities.

    • box coordinates.

The first one is a layer with the name 6849/sink_port_0, and rest are outputs from the DetectionOutput layer.