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hi
I tried to implement face recognition using openvino with MYRIAD plugin .Below zip file has complete source which i implemented using the reference of
https://github.com/davidsandberg/facenet and https://github.com/kuberlab/facenet i executed using
20170512-110547 model
ubuntu 16.04
openvino 2019.1.144
Face detection was good but with face recognition i'm not getting proper result like mismatches and least accuracy .
how can i increase my accuracy ,i tried with passing scale value mean values .I need everything should run on NCS2 stick not on host machine .could u help me with this.
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Dear kvgr, deepika,
As we have discussed before, you are likely not telling Model Optimizer about the pre-processing which Facenet does and that is why you're experiencing accuracy issues. Model Optimizer cannot know about this pre-processing. The person who builds the model must know the details about image pre-processing.
Please carefully study the following online resources to find out more about Facenet pre-processing:
https://kpzhang93.github.io/MTCNN_face_detection_alignment/index.html
https://github.com/kpzhang93/MTCNN_face_detection_alignment
https://github.com/davidsandberg/facenet/tree/master/src/align
https://machinelearningmastery.com/how-to-manually-scale-image-pixel-data-for-deep-learning/
Hope it helps,
Thanks,
Shubha
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Dear kvgr, deepika,
I found your other thread regarding Facenet accuracy issue and it seems that for MYRIAD devices:
The only solution is to train the model on Inception resnet v2 or to use compute stick myriad 1 until intel allow support for Incpetoin resnet v1 on new myriad devices.
Inception resnet v1 is not supported on NCS2. I have filed a feature request for this actually.
Thanks for sharing with the OpenVino community and I appreciate your patience !
Shubha
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hi shubha,
Thankyou for information.Ive found inceptionresnetv2 checkpoint file but not pb/pbtxt . could u help me to find inceptionresnetv2 pb file if possible share me the pb file.
thanks®ards
Deepika
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Dear kvgr, deepika,
How about downloading it from the Model Optimizer Tensorflow Supported List ?
Thanks,
Shubha
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