PINTO_model_zoo/099_efficientnet_anomaly_detection_segmentation/convert_script.txt at main · PINTO0309/PINTO_model_zoo · GitHub

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python3 ${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/mo.py \
 --input_model onnx/efficientnet_anomaly_detection_segmentation.onnx \
 --input x.1 \
 --output_dir openvino/efficientnet_anomaly_detection_segmentation/FP32 \
 --data_type FP32

python3 ${INTEL_OPENVINO_DIR}/deployment_tools/model_optimizer/mo.py \
 --input_model onnx/efficientnet_anomaly_detection_segmentation.onnx \
 --input x.1 \
 --output_dir openvino/efficientnet_anomaly_detection_segmentation/FP16 \
 --data_type FP16

docker run --gpus all -it --rm \
    -v `pwd`:/workspace/resources \
    -e LOCAL_UID=$(id -u $USER) \
    -e LOCAL_GID=$(id -g $USER) \
    pinto0309/openvino2tensorflow:latest bash

source /opt/intel/openvino_2021/bin/setupvars.sh

cd resources

openvino2tensorflow \
--model_path openvino/efficientnet_anomaly_detection_segmentation/FP32/efficientnet_anomaly_detection_segmentation.xml \
--output_pb True

pb_to_saved_model \
--pb_file_path saved_model/model_float32.pb \
--inputs inputs:0 \
--outputs Identity:0

saved_model_to_tflite \
--saved_model_dir_path saved_model \
--output_no_quant_float32_tflite True \
--output_weight_quant_tflite True \
--output_float16_quant_tflite True \
--output_integer_quant_tflite True \
--string_formulas_for_normalization 'data / 255' \
--output_tfjs True \
--output_tftrt True \
--output_coreml True

saved_model_to_tflite \
--saved_model_dir_path saved_model \
--output_onnx True \
--onnx_opset 13

${INTEL_OPENVINO_DIR}/deployment_tools/inference_engine/lib/intel64/myriad_compile \
 -m saved_model/openvino/FP16/efficientnet_anomaly_detection_segmentation.xml \
 -VPU_NUMBER_OF_SHAVES 4 \
 -VPU_NUMBER_OF_CMX_SLICES 4 \
 -o saved_model/openvino/myriad/efficientnet_anomaly_detection_segmentation.blob