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- OS: Windows 10 pro
- CPU: Intel(R) Core(TM) i5-7500 CPU @3.40GHz
- GPU: None
- OpenVINO: 2020.1
- python: 3.7.6
- tensorflow: 1.15.0
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Hi everyone,
When wanting to use "mask_rcnn_resnet50_atrous_coco_2018_01_28" from model zoo and freezing it, I met a problem below:
There are my input arguments
- --input_model : <folder path>/frozen_inference_graph.pb
- --output_dir : <folder path>
- --input_checkpoint : <folder path>/checkpoint
- --tensorflow_use_custom_operations_config : <folder>/mask_rcnn_support.json
- --tensorflow_object_detection_api_pipeline_config : <folder>/pipeline.config
Error :
Anyone who also meets the same problem can help resolve it. Thanks !!
I have debugged on the model convert several days ....
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Hi Liao,
I have just tried to convert this model using model optimizer and was able to successfully obtain the IR using the follwing command:
python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_model <path-to-model>/frozen_inference_graph.pb --tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json --tensorflow_object_detection_api_pipeline_config <path-to-model>/pipeline.config -o <path-to-save-output>
Please try again after removing the --input_checkpoint argument.
Regards,
Jaivin
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Hi Jaivin,
I have tried what you said. But still cannot work and output the same error.
There is my input argument below:
python mo_tf.py --input_model C:/Users/<username>/Downloads/Release/mask_rcnn_inception_v2_coco_2018_01_28-1/inference_graph/frozen_inference_graph.pb --output_dir C:/Users/<username>/Downloads/Release/mask_rcnn_inception_v2_coco_2018_01_28-1/inference_graph/ --tensorflow_use_custom_operations_config C:/"Program Files (x86)"/IntelSWTools/openvino_2020.1.033/deployment_tools/model_optimizer/extensions/front/tf/mask_rcnn_support.json
I run it with --log_level DEBUG and show these message.
By the way, I run mo_tf.py under the virtual environment. I don't know that it's a problem i meet
Best Regards.
Jeff
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Hi Jeff,
On the command you have mentioned, --tensorflow_object_detection_api_pipeline_config parameter has not been used. Please use the parameter and try again.
Regards,
Jaivin
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