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Hi,
I'm working on running blazeface and posenet models with inference engine. First, I used the following command to convert them:
- For Posenet:
python3 mo_tf.py --input_model posenet.pb --output_dir /users/thibault/Documents/posenet --data_type FP32 --disable_nhwc_to_nchw
- For Blazeface :
python3 mo_tf.py --input_model blazeface.pb --output_dir /users/thibault/Documents/posenet --data_type FP32
After running this model I get a bad display of landmarks for both two models. The code is good but I guess I missed something during tensorflowLite model conversion.
If someone has an idea how to convert correctly this two models.
Thanks
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Greetings,
If possible could you provide the link to the resources of blazenet and posenet so I could try to convert them myself?
Fyi, this is the official documentation on how to convert Tensorflow model:
Sincerely,
Iffa
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Thanks for your reply,
I found the frozen models from here with script download:
Blazeface:
https://github.com/PINTO0309/PINTO_model_zoo/tree/master/30_BlazeFace/01_float32
Posenet:
https://github.com/PINTO0309/PINTO_model_zoo/tree/master/03_posenet/03_posenet/01_float32
I just noticed that the posenet model has been converted for openvino (FP32 and FP16) from this link 4 days ago. I'm going to try with this one too:
https://github.com/PINTO0309/PINTO_model_zoo/tree/master/03_posenet/03_posenet/05_openvino
Regards
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Greetings,
You can actually get the readily converted model in IR form by running the download script inside openvino folder (in Blazenet/Posenet folder).
Since this came with the Blazenet and Posenet model's package and clearly stated this is for openvino, this should already been correctly converted.
for Blazenet you will get 2 folders (face detection back and front)
Same thing applies for Posenet
Sincerely,
Iffa
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Greetings,
Intel will no longer monitor this thread since we have provided a solution. If you need any additional information from Intel, please submit a new question.
Sincerely,
Iffa

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