INNER CODE UNIT · Python
validation_steps
atulapra/Emotion-detection · src/emotions.py:97
validation_steps=num_val // batch_size)
plot_model_history(model_info)
model.save_weights('model.h5')
# emotions will be displayed on your face from the webcam feed
elif mode == "display":
model.load_weights('model.h5')
# prevents openCL usage and unnecessary logging messages
cv2.ocl.setUseOpenCL(False)
# dictionary which assigns each label an emotion (alphabetical order)
emotion_dict = {0: "Angry", 1: "Disgusted", 2: "Fearful", 3: "Happy", 4: "Neutral", 5: "Sad", 6: "Surprised"}
# start the webcam feed
cap = cv2.VideoCapture(0)
while True:
# Find haar cascade to draw bounding box around face