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I followed this documentation for converting yolov3 model to IR. The step for generating *.pb file success.
However I encounter this error while running model_optimizer:
python mo_tf.py --input_model frozen_darknet_yolov3_model.pb --tensorflow_use_custom_operations_config extensions\front\tf\yolo_v3.json --input_shape [1,416,416,3]
Model Optimizer arguments:
Common parameters:
- Path to the Input Model: frozen_darknet_yolov3_model.pb
- Path for generated IR: openvino\deployment_tools\model_optimizer\.
- IR output name: frozen_darknet_yolov3_model
- Log level: ERROR
- Batch: Not specified, inherited from the model
- Input layers: Not specified, inherited from the model
- Output layers: Not specified, inherited from the model
- Input shapes: [1,416,416,3]
- Mean values: Not specified
- Scale values: Not specified
- Scale factor: Not specified
- Precision of IR: FP32
- 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
- Path to model dump for TensorBoard: None
- List of shared libraries with TensorFlow custom layers implementation: 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: C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\extensions\front\tf\yolo_v3.json
Model Optimizer version: 2019.1.1-83-g28dfbfd
C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\middle\passes\fusing\decomposition.py:65: RuntimeWarning: invalid value encountered in sqrt
scale = 1. / np.sqrt(variance.value + eps)
[ ERROR ] -------------------------------------------------
[ ERROR ] ----------------- INTERNAL ERROR ----------------
[ ERROR ] Unexpected exception happened.
[ ERROR ] Please contact Model Optimizer developers and forward the following information:
[ ERROR ]
[ ERROR ] Traceback (most recent call last):
File "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\main.py", line 312, in main
return driver(argv)
File "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\main.py", line 263, in driver
is_binary=not argv.input_model_is_text)
File "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\pipeline\tf.py", line 141, in tf2nx
graph_clean_up_tf(graph)
File "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\middle\passes\eliminate.py", line 186, in graph_clean_up_tf
graph_clean_up(graph, ['TFCustomSubgraphCall', 'Shape'])
File "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\middle\passes\eliminate.py", line 181, in graph_clean_up
add_constant_operations(graph)
File "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\middle\passes\eliminate.py", line 145, in add_constant_operations
Const(graph, dict(value=node.value, shape=np.array(node.value.shape))).create_node_with_data(data_nodes=node)
File "C:\Program Files (x86)\IntelSWTools\openvino\deployment_tools\model_optimizer\mo\ops\op.py", line 207, in create_node_with_data
[np.array_equal(old_data_value[id], data_node.value) for id, data_node in enumerate(data_nodes)])
AssertionError[ ERROR ] ---------------- END OF BUG REPORT --------------
[ ERROR ] -------------------------------------------------
Model Optimizer commands:
python mo_tf.py --input_model frozen_darknet_yolov3_model.pb --tensorflow_use_custom_operations_config extensions\front\tf\yolo_v3.json --input_shape [1,416,416,3]
Link to *.pb file
https://drive.google.com/open?id=1r_CFzHeoOq8HdBK_3VtgB_23UJgai0Ct
Link Copied

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