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realtime_facial_expression.py
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realtime_facial_expression.py
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#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Sat Jun 3 15:36:49 2017
@author: adam
"""
import cv2
import numpy as np
from keras.models import load_model
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_alt2.xml')
video_capture = cv2.VideoCapture(0)
model = load_model('keras_model/model_5-49-0.62.hdf5')
target = ['angry','disgust','fear','happy','sad','surprise','neutral']
font = cv2.FONT_HERSHEY_SIMPLEX
while True:
# Capture frame-by-frame
ret, frame = video_capture.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray,scaleFactor=1.1)
# Draw a rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2,5)
face_crop = frame[y:y+h,x:x+w]
face_crop = cv2.resize(face_crop,(48,48))
face_crop = cv2.cvtColor(face_crop, cv2.COLOR_BGR2GRAY)
face_crop = face_crop.astype('float32')/255
face_crop = np.asarray(face_crop)
face_crop = face_crop.reshape(1, 1,face_crop.shape[0],face_crop.shape[1])
result = target[np.argmax(model.predict(face_crop))]
cv2.putText(frame,result,(x,y), font, 1, (200,0,0), 3, cv2.LINE_AA)
# Display the resulting frame
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()