Converting an ONNX Faster R-CNN Model

The instructions below are applicable only to the Faster 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 FasterRCNN-10.onnx \
   --input_shape [1,3,800,800] \
   --input 0:2 \
   --mean_values [102.9801,115.9465,122.7717] \
   --transformations_config front/onnx/faster_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 Faster R-CNN article.

1. Interpret the outputs of the generated IR: class indices, probabilities and box coordinates. Below are the outputs from the “DetectionOutput” layer:

   • class indices.

   • probabilities.

   • box coordinates.