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6. Face Recognition using Tensorflow Lite demo
This application demo uses Haar Feature-based Cascade Classifiers for real time face
detection. The pre-trained Haar Feature-based Cascade Classifiers for face, named as XML.
TensorFlow Lite implementation for MobileFaceNets.
The MobileFaceNets is re-trained with a smaller batch size and input size to get a higher
performance on a host PC. The trained model is loaded as a source file in this demo.
Steps to run Tf_based Face Recognition Demo:
Run
/run/media/mmcblk1p3/ARROW_DEMOS/run_ml_demos.sh script and select
appropriate option
,then select Node Entry e.g
/0/1/2/3/4
.
# sh /run/media/mmcblk1p3/ARROW_DEMOS/run_ml_demos.sh
######## Welcome to ML Demos [AI Corowd Count/Object detection/Face Recognition/Speech
Recognition/Arm NN] ##########
Prerequisite: Have you run <setup_ml_demo.sh>?
Press: (y/n)
y
Choose the option from following
Press 1 : AI Crowd Count
Press 2 : Object Detection
Press 3 : Face Recognition
Press 4 : Speech Recognition
Figure 19: Tensorflow based Face Recognition demo run screen
Содержание iMX8XML
Страница 6: ...Figure 2 Hardware Setup...
Страница 15: ...Figure 7 Crowd Count Pre Captured Mode Figure 8 Crowd Count Live Mode...
Страница 41: ...Figure 18 Pylon Viewer App display issue...
Страница 52: ...Figure 26 No Camera connected error...