Intel® Distribution of OpenVINO™ Toolkit
Community assistance about the Intel® Distribution of OpenVINO™ toolkit, OpenCV, and all aspects of computer vision-related on Intel® platforms.

The model of object_detection_yolov3

林__云泽
Beginner
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I'm using the openvino_R1.

when I want to test the objection_detection_demo_yolo v3,I can't find its model.

I can't get its information or model link in the readme.md.

How can I get the model of this demo ?

 

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HemanthKum_G_Intel
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Hi,

I have created collateral for this. Refer - https://github.com/vijnasu/OpenVINO-Experiments/tree/master/Yolov3

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林__云泽
Beginner
494 Views

Hi!

Thanks for your help!

But when I can do the " Convert YOLOv3 TensorFlow Model to the IR for CPU" ,it return error:(I'm using ubuntu 16.04)

root@UP2:/opt/intel/2019_r1/openvino_2019.1.094/deployment_tools/model_optimizer# ./mo_tf.py --input_model /home/terasic/Desktop/frozen_darknet_yolov3_model.pb --tensorflow_use_custom_operations_config /home/terasic/Desktop/yolo_v3.json --input_shape [1,416,416,3]
Model Optimizer arguments:
Common parameters:
    - Path to the Input Model:     /home/terasic/Desktop/frozen_darknet_yolov3_model.pb
    - Path for generated IR:     /opt/intel/2019_r1/openvino_2019.1.094/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:     /home/terasic/Desktop/yolo_v3.json
Model Optimizer version:     2019.1.0-341-gc9b66a2
[ ERROR ]  -------------------------------------------------
[ ERROR ]  ----------------- INTERNAL ERROR ----------------
[ ERROR ]  Unexpected exception happened.
[ ERROR ]  Please contact Model Optimizer developers and forward the following information:
[ ERROR ]  problem writing element 2181120 to file
[ ERROR ]  Traceback (most recent call last):
  File "/opt/intel/2019_r1/openvino_2019.1.094/deployment_tools/model_optimizer/mo/main.py", line 312, in main
    return driver(argv)
  File "/opt/intel/2019_r1/openvino_2019.1.094/deployment_tools/model_optimizer/mo/main.py", line 263, in driver
    is_binary=not argv.input_model_is_text)
  File "/opt/intel/2019_r1/openvino_2019.1.094/deployment_tools/model_optimizer/mo/pipeline/tf.py", line 228, in tf2nx
    meta_info=meta_info)
  File "/opt/intel/2019_r1/openvino_2019.1.094/deployment_tools/model_optimizer/mo/pipeline/common.py", line 127, in prepare_emit_ir
    serialize_constants(graph, bin_file)
  File "/opt/intel/2019_r1/openvino_2019.1.094/deployment_tools/model_optimizer/mo/back/ie_ir_ver_2/emitter.py", line 42, in serialize_constants
    serialize_constants_recursively(graph, bin_file, data_type, bin_hashes)
  File "/opt/intel/2019_r1/openvino_2019.1.094/deployment_tools/model_optimizer/mo/back/ie_ir_ver_2/emitter.py", line 59, in serialize_constants_recursively
    blob.tofile(bin_file)
OSError: problem writing element 2181120 to file

[ ERROR ]  ---------------- END OF BUG REPORT --------------
[ ERROR ]  -------------------------------------------------

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