Converting a PyTorch Cascade RCNN R-101 Model#

Danger

The code described here has been deprecated! Do not use it to avoid working with a legacy solution. It will be kept for some time to ensure backwards compatibility, but you should not use it in contemporary applications.

This guide describes a deprecated conversion method. The guide on the new and recommended method can be found in the Python tutorials.

The goal of this article is to present a step-by-step guide on how to convert a PyTorch Cascade RCNN R-101 model to OpenVINO IR. First, you need to download the model and convert it to ONNX.

Downloading and Converting Model to ONNX#

  • Clone the repository :

    git clone https://github.com/open-mmlab/mmdetection
cd mmdetection

    Note

    To set up an environment, refer to the instructions.

  • Download the pre-trained model. The model is also available here.

  • To convert the model to ONNX format, use this script.

    python3 tools/deployment/pytorch2onnx.py configs/cascade_rcnn/cascade_rcnn_r101_fpn_1x_coco.py cascade_rcnn_r101_fpn_1x_coco_20200317-0b6a2fbf.pth --output-file    cascade_rcnn_r101_fpn_1x_coco.onnx

The script generates ONNX model file cascade_rcnn_r101_fpn_1x_coco.onnx in the directory tools/deployment/. If required, specify the model name or output directory, using --output-file <path-to-dir>/<model-name>.onnx.

Converting an ONNX Cascade RCNN R-101 Model to OpenVINO IR#

mo --input_model cascade_rcnn_r101_fpn_1x_coco.onnx --mean_values [123.675,116.28,103.53] --scale_values [58.395,57.12,57.375]