MXnet 转 OpenVino，在树莓派上做的图片推理

[在使用Movidius的模型优化器转换模型之前，需要先用MXNet的deploy.py将模型转换成部署模式，然后才能用movidius的优化器转换]

https://github.com/apache/incubator-mxnet/blob/master/example/ssd/deploy.py

cd ~
git clone https://github.com/apache/incubator-mxnet

mv tmp/*-0000.params tmp/ssd_resnet50_512-0000.params
mv tmp/*-symbol.json tmp/ssd_resnet50_512-symbol.json

python3 incubator-mxnet/example/ssd/deploy.py --network resnet50 --data-shape 512 --num-class 5 --prefix tmp/ssd_

cd /opt/intel/openvino/deployment_tools/model_optimizer

python3 mo_mxnet.py --input_model ssd_resnet50_512-0000.params --input_shape [1,3,512,512]

python3 mo_mxnet.py --input_model ssd_resnet50_512-0000.params --input_shape [1,3,512,512] --data_type=FP16

参考下面的blog： https://github.com/awslabs/amazon-sagemaker-examples/blob/master/introduction_to_amazon_algorithms/object_detection_birds/object_detection_birds.ipynb

树莓派在计算棒上做的推理