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deeplearning@deep-learning-virtual-machine:/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer$ sudo python3 mo.py --input_model ../../../../../home/deeplearning/Downloads/faster_rcnn_models/ZF_faster_rcnn_final.caffemodel --input_proto ../../../../../home/deeplearning/Downloads/test.prototxtModel Optimizer argumentsBatch: 1Precision of IR: FP32Enable fusing: TrueEnable gfusing: TrueNames of input layers: inherited from the modelPath to the Input Model: ../../../../../home/deeplearning/Downloads/faster_rcnn_models/ZF_faster_rcnn_final.caffemodelInput shapes: inherited from the modelLog level: ERRORMean values: ()IR output name: inherited from the modelNames of output layers: inherited from the modelPath for generated IR: /opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizerReverse input channels: FalseScale factor: NoneScale values: ()Version: 0.3.75.d6bae621Input proto file: ../../../../../home/deeplearning/Downloads/test.prototxtPath to CustomLayersMapping.xml: extensions/front/caffe/CustomLayersMapping.xmlPath to a mean file:Offsets for a mean file: None[ ERROR ] -------------------------------------------------[ ERROR ] ----------------- INTERNAL ERROR ----------------[ ERROR ] Unexpected exception happened.[ ERROR ] Please contact Model Optimizer developers and forward the following information:[ ERROR ] 'Python'[ ERROR ] Traceback (most recent call last):File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/main.py", line 222, in mainreturn driver(argv)File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/main.py", line 202, in drivercustom_layers_mapping_path=custom_layers_mapping_path)File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/pipeline/caffe.py", line 106, in driverextract_node_attrs(graph, lambda node: caffe_extractor(node, check_for_duplicates(caffe_type_extractors)))File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/front/extractor.py", line 413, in extract_node_attrssupported, new_attrs = extractor(Node(graph, node))File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/pipeline/caffe.py", line 106, in <lambda>extract_node_attrs(graph, lambda node: caffe_extractor(node, check_for_duplicates(caffe_type_extractors)))File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/front/caffe/extractor.py", line 127, in caffe_extractorresult.update(caffe_type_extractors[name](node))File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/front/common/register_custom_ops.py", line 95, in <lambda>node, cls, disable_omitting_optional, enable_flattening_optional_params),File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/front/common/register_custom_ops.py", line 27, in extension_extractorsupported = ex.extract(node)File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/extensions/front/caffe/python_proposal-ext.py", line 13, in extractOp.get_op_class_by_name(__class__.op).update_node_stat(node, attrs)File "/opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer/mo/ops/op.py", line 185, in get_op_class_by_namereturn __class__.registered_ops[name]KeyError: 'Python'[ ERROR ] ---------------- END OF BUG REPORT --------------[ ERROR ] -------------------------------------------------
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Hi Yogesh,
This model contains Proposal layer with type 'Python'.
Currently Model Optimizer provides limited support to such layers.
However, you can still work with this model. In particular, you need to use additional extensions that should be taken from the Inference Engine sample.
Please refer to this document with the details: https://software.intel.com/en-us/articles/OpenVINO-ModelOptimizer#extending-the-model-optimizer-with-new-primitives
In particular, try to use the following command (taken from https://software.intel.com/en-us/articles/OpenVINO-InferEngine#inpage-nav-8-4-2):
python3 ${MO_ROOT_PATH}/mo_caffe.py --input_model <path_to_model>/VGG16_faster_rcnn_final.caffemodel --input_proto <path_to_model>/deploy.prototxt --extensions <path_to_object_detection_sample>/fasterrcnn_extensions |
Please let me know if you still face the problem.
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Hi Alexander,
Thanks for the reply.
I tried to use model optimizer with additional extensions. The Process is getting killed after 1~3 minutes.
yment_tools/model_optimizer$ sudo python3 mo_caffe.py --input_model ../../../../../home/deeplearning/Downloads/faster_rcnn_models/VGG16_faster_rcnn_final.caffemodel --input_proto ../../../../../home/deeplearning/Downloads/test.prototxt --extensions ../../deployment_tools/inference_engine/samples/object_detection_sample/fasterrcnn_extensions/ [sudo] password for deeplearning: Model Optimizer arguments Batch: 1 Precision of IR: FP32 Enable fusing: True Enable gfusing: True Names of input layers: inherited from the model Path to the Input Model: ../../../../../home/deeplearning/Downloads/faster_rcnn_models/VGG16_faster_rcnn_final.caffemodel Input shapes: inherited from the model Log level: ERROR Mean values: () IR output name: inherited from the model Names of output layers: inherited from the model Path for generated IR: /opt/intel/computer_vision_sdk_2018.1.249/deployment_tools/model_optimizer Reverse input channels: False Scale factor: None Scale values: () Version: 0.3.75.d6bae621 Input proto file: ../../../../../home/deeplearning/Downloads/test.prototxt Path to CustomLayersMapping.xml: extensions/front/caffe/CustomLayersMapping.xml Path to a mean file: Offsets for a mean file: None Killed
Does model Optimizer requires some specific set of hardware? I am trying to run it inside a 4GB 4Core Ubuntu 16.04 Vm.
Regards
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Hi Yogesh,
Have you used these links for ZF Faster-RCNN?
Prototxt: https://raw.githubusercontent.com/rbgirshick/py-faster-rcnn/master/models/pascal_voc/ZF/faster_rcnn_end2end/test.prototxt
Caffemodel: https://dl.dropboxusercontent.com/s/o6ii098bu51d139/faster_rcnn_models.tgz?dl=0
If not, please double check with those links. Are you still facing same issues?
Model Optimizer is a light-weight tool and does not require any advanced hardware.
Are you running on Windows?
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I am able to test using the below command from this link :-
python3 mo_caffe.py --input_model /opt/intel/computer_vision_sdk/deployment_tools/model_downloader/object_detection/common/mobilenet-ssd/caffe/mobilenet-ssd.caffemodel -o $SV/object-detection/mobilenet-ssd/FP32 --scale 256 --mean_values [127,127,127]
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