Hi all together,
i just created a "Faster R-CNN ResNet 50" IR with OpenVINO computer_vision_sdk_2018.3.343 as shown in your documentation: ./deployment_tools/documentation/docs/TensorFlowObjectDetectionFasterRCNN.html
The frozen inference graph was downloaded from the link shown in your Tutorial: faster_rcnn_resnet50_lowproposals_coco_2018_01_28.tar.gz
The conversion is done with the command shown in your tutorial too, modified with --data_type FP16. I used FP16 because MYRIAD only supports FP16. The command i used is this:
~/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer$ ./mo.py --input_model=~/Desktop/faster_rcnn/frozen_inference_graph.pb --output=detection_boxes,detection_scores,num_detections --tensorflow_use_custom_operations_config extensions/front/tf/legacy_faster_rcnn_support.json --output_dir=~/Desktop/faster_rcnn/IR --model_name frozen_inference_graph_FP16 --data_type FP16
The full output of the Conversion is this:
Model Optimizer arguments: Common parameters: - Path to the Input Model: /home/up-board/Desktop/faster_rcnn/frozen_inference_graph.pb - Path for generated IR: /home/up-board/Desktop/faster_rcnn/IR - IR output name: frozen_inference_graph_FP16 - Log level: ERROR - Batch: Not specified, inherited from the model - Input layers: Not specified, inherited from the model - Output layers: detection_boxes,detection_scores,num_detections - Input shapes: Not specified, inherited from the model - Mean values: Not specified - Scale values: Not specified - Scale factor: Not specified - Precision of IR: FP16 - Enable fusing: True - Enable grouped convolutions fusing: True - Move mean values to preprocess section: False - Reverse input channels: False TensorFlow specific parameters: - Input model in text protobuf format: False - Offload unsupported operations: False - Path to model dump for TensorBoard: None - Update the configuration file with input/output node names: None - Use configuration file used to generate the model with Object Detection API: None - Operations to offload: None - Patterns to offload: None - Use the config file: /home/up-board/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/extensions/front/tf/legacy_faster_rcnn_support.json Model Optimizer version: 220.127.116.1135e231 WARNING: the "PreprocessorReplacement" is a legacy replacer that will be removed in the future release. Please, consider using replacers defined in the "extensions/front/tf/ObjectDetectionAPI.py" The Preprocessor block has been removed. Only nodes performing mean value subtraction and scaling (if applicable) are kept. WARNING: the "TFObjectDetectionAPIFasterRCNNProposalAndROIPooling" is a legacy replacer that will be removed in the future release. Please, consider using replacers defined in the "extensions/front/tf/ObjectDetectionAPI.py" WARNING: the "SecondStagePostprocessorReplacement" is a legacy replacer that will be removed in the future release. Please, consider using replacers defined in the "extensions/front/tf/ObjectDetectionAPI.py" The graph output nodes "num_detections", "detection_boxes", "detection_classes", "detection_scores" have been replaced with a single layer of type "Detection Output". Refer to IR catalogue in the Inference Engine documentation for information about this layer. The "object_detection_sample_ssd" sample can be used to run the generated model. /home/up-board/intel/computer_vision_sdk_2018.3.343/deployment_tools/model_optimizer/mo/front/common/partial_infer/slice.py:90: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result. value = value[slice_idx] [ SUCCESS ] Generated IR model. [ SUCCESS ] XML file: /home/up-board/Desktop/faster_rcnn/IR/frozen_inference_graph_FP16.xml [ SUCCESS ] BIN file: /home/up-board/Desktop/faster_rcnn/IR/frozen_inference_graph_FP16.bin [ SUCCESS ] Total execution time: 124.86 seconds.
In a python script i load the network into PlugIn "GPU" and its working well. If i change the PlugIn to "MYRIAD" the following Exception is thrown:
Traceback (most recent call last): File "~/InferenceEngine.py", line 43, in load_network self.exec_network = self.plugin.load(network=self.network) File "ie_api.pyx", line 237, in inference_engine.ie_api.IEPlugin.load File "ie_api.pyx", line 249, in inference_engine.ie_api.IEPlugin.load RuntimeError: [VPU] Reshape input or output reshape_4d_ has invalid batch /teamcity/work/scoring_engine_build/releases_openvino-2018-r3/ie_bridges/python/inference_engine/ie_api_impl.cpp:226
Does someone know whats happening? Is MYRIAD not supporting the models shown in the tutorials?
indeed Myriad does not support TF Faster RCNN. It is actually indicated in our documentation: https://software.intel.com/en-us/articles/OpenVINO-Using-TensorFlow#inpage-nav-2-1 , but we definitely can make it clearer in our tutorial.