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Error :
[ ERROR ] Shape [-1 -1 -1 3] is not fully defined for output 0 of "image_tensor". Use --input_shape with positive integers to override model input shapes.
[ ERROR ] Cannot infer shapes or values for node "image_tensor".
[ ERROR ] Not all output shapes were inferred or fully defined for node "image_tensor".
For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_tools/documentation/docs/MO_FAQ.html), question #40.
[ ERROR ]
[ ERROR ] It can happen due to bug in custom shape infer function <function tf_placeholder_ext.<locals>.<lambda> at 0x000001F217D4B1E0>.
[ ERROR ] Or because the node inputs have incorrect values/shapes.
[ ERROR ] Or because input shapes are incorrect (embedded to the model or passed via --input_shape).
[ ERROR ] Run Model Optimizer with --log_level=DEBUG for more information.
[ ERROR ] Exception occurred during running replacer "REPLACEMENT_ID" (<class 'extensions.middle.PartialInfer.PartialInfer'>): Stopped shape/value propagation at "image_tensor" node.
For more information please refer to Model Optimizer FAQ (<INSTALL_DIR>/deployment_tools/documentation/docs/MO_FAQ.html), question #38.
I have trained the model on my own labelled dataset....so its' modified mobilenet
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Hi abhi,
The issue may be with your code used to inference, did you start from scratch or based it off one of our sample apps?
I was able to get detect the person in your image using one of our sample demos. To build the samples, run the build_sample.sh scrip in the <openvino>/inference_engine/samples directory.
I used the following command to run your model and image with the sample app.
Python3 ~/inference_engine_samples_build/intel64/Release/object_detection_sample_ssd -m frozen_inference_graph.xml -i image.jpeg -d MYRIAD
Regards,
Jesus
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@Intel_Jesus also can you attach your .xml converted file so I can test if the .xml file was not corrupted?
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@Intel_Jesus downloaded openvino r1 and extracted it....there ain't any object_detection_demo_ssd_async.py
It's object_detection_demo_ssd_async.hpp & cpp file
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Hi abhi,
I apologize for the confusion, let me explain and try to answer your questions.
In my previous response, I recommended installing R2 2019 and using the sample code from R1.1 2019. When you run the sample code it will use the installed version for inference.
The build_samples.sh script will build all the C++ examples, in your command you are trying to execute a C++ application using Python. You can run the compiled C++ example by using the following command.
./object_detection_sample_ssd -d MYRIAD -m <model> -i <image/camera>
In the samples directory where you found the build_samples.sh script, there is a folder called python_samples. You can use those samples if you want to run the sample in Python using the following command.
python3 object_detection_demo_ssd_async.py -d MYRIAD -m <model> -i <image/camera>
Regards,
Jesus
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