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Use Haar classified and Keras to detected the face with CNN.

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face_detection_CNN

Use CNN model to classify the users face and combine with Arduino. image

First one, we must to create 2 empty folders, named "data" and "model", which will be saved parameter files and used by the codes.

Second, use the codes to follow the next steps:

step01: Run createdb.py to create a database.

step02: Use catch_pic_db.py to catch user face pictures and register into  step01 database.

step03: Use showdb.py to make sure the database you have to load in.

step04: Modify the prepare_data.py file, which in load_dataset() function with many labels(e.g. if you have 5 users, you can modify the 5 labels in label_dict{[labels]}).

step05: Run the tf1_train.py, remember to modify parameter about nb_classes, batch_size, and nb_epoch, also can choose data_augmentation true or false.

step06: Remember prepare a Arduino to set the led then create a empty folder named "led_test" and put the led_test.ino in it.

step07: Run the face_predict_gui.py and execute the GUI buttons.

step08: Finally, use showdb.py code to make sure the database to show users have checked in successfully.

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Use Haar classified and Keras to detected the face with CNN.

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