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FaceTest.py
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FaceTest.py
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import numpy as np
import keras
import cv2
import tensorflow as tf
import matplotlib.pyplot as plt
import os
def load_images_from_folder(folder):
images = []
for filename in os.listdir(folder):
img = cv2.imread(os.path.join(folder,filename))
if img is not None:
images.append(img)
return images
model=keras.models.load_model('eye_state.h5')
def picture_anal(img):
#make the dface and eyes detectors
faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_alt.xml')
eyeCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces=faceCascade.detectMultiScale(gray, 1.1, 4)
if len(faces)<1:
return 0
for (x, y, w, h) in faces:
gray = gray[y:y+int(h*0.6), x:x+w]
img = img[y:y+int(h*0.6), x:x+w]
#get the first 2 instances of eyes
eyes = eyeCascade.detectMultiScale(gray, 1.3, 6)
#draw the eye borders and show it
img2=img.copy()
if len(faces)<1:
return 0
for (x, y, w, h) in eyes:
cv2.rectangle(img2, (x,y), (x+w, y+h), (0, 255, 0), 2)
eyeCascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_eye.xml')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
eyes = eyeCascade.detectMultiScale(gray, 1.1, 4)
for x, y,w, h in eyes:
print(x, y, w, h)
roi_gray = gray[int(y*0.8):y+int(h*1.1), int(x*1):x+int(w*1.2)]
roi_color = img[int(y*0.8):y+int(h*1.1), int(x*1):x+int(w*1.2)]
eyess = eyeCascade.detectMultiScale(roi_gray)
if len(eyess) == 0:
print("eyes not detected")
else:
for ex, ey, ew, eh in eyess :
eyes_roi = roi_color
final_img = cv2.resize(eyes_roi, (64,64))
final_img=cv2.cvtColor(final_img, cv2.COLOR_BGR2GRAY)
final_img = np.expand_dims(final_img, axis=0)
final_img = final_img/255.0
if np.argmax(model.predict(final_img))==0:#0 is closed eyes, 1 is open
return 0
return 1