I wanted to convert MXNet RetinaFace-MobileNet0.25 model (https://github.com/deepinsight/insightface/tree/master/RetinaFace#third-party-models) to OpenVINO IR and I got that by using the following command:
python deployment_tools\model_optimizer\mo_mxnet.py --input_model mxnet_models\RetinaFace\mnet.25-0000.params --input_shape (1,3,640,640) --output_dir openvino_models
and it was successfully converted.
After that I tested inference on both mxnet model and openvino model to check if the outputs were the same. However the output sizes for MXNet are:
* 88 for width and height;
* 44 for width and height;
* 22 for width and height.
And the OpenVINO output sizes are:
* 80 for width and height;
* 40 for width and height;
* 20 for width and height.
The first thing I would check is to make sure all the layers of the model are supported by OpenVINO.
Here you can see the details about the MXNet layers
Then it would be a good idea to check layer by layer if the input/outputs are correct or at which point there's something wrong.
MobileNet0.25 topology is not officially supported by OpenVINO and RetinaFace-MobileNet0.25 model has not been validated for inferencing performance as well.
More information is available at the following page:
Also, I would encourage you to try out Intel® Distribution of OpenVINO™ Toolkit version 2020.4, which is a vastly improved version with latest features and leading performance.