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pregnentfaceanalysis.py

+
+
+# import the necessary packages
+from scipy.spatial import distance as dist
+from imutils.video import FileVideoStream
+from imutils.video import VideoStream
+from imutils import face_utils
+import argparse
+import imutils
+import time
+import dlib
+import cv2
+
+# Load the cascades
+face_cascade = cv2.CascadeClassifier('frontalface_cascade.xml')
+eye_cascade = cv2.CascadeClassifier('eyes_cascade.xml')
+smile_cascade = cv2.CascadeClassifier('Smile_cascade.xml')
+
+# Defining a function that will do the detections
+def detect(gray, frame):
+    faces = face_cascade.detectMultiScale(gray, 1.3, 5)
+    for (x, y, w, h) in faces:
+        cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2)
+        roi_gray = gray[y:y+h, x:x+w]
+        roi_color = frame[y:y+h, x:x+w]
+        eyes = eye_cascade.detectMultiScale(roi_gray, 1.1, 22)
+        for (ex, ey, ew, eh) in eyes:
+            cv2.rectangle(roi_color, (ex, ey), (ex+ew, ey+eh), (0, 255, 0), 2)
+        smiles = smile_cascade.detectMultiScale(roi_gray,1.7, 19)
+        for (sx, sy, sw, sh) in smiles:
+            cv2.rectangle(roi_color, (sx, sy), (sx+sw, sy+sh), (0, 0, 255), 5)
+    return frame
+
+# Doing some Face Recognition with the webcam
+video_capture = cv2.VideoCapture(0)
+while True:
+    _, frame = video_capture.read()
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    canvas = detect(gray, frame)
+    cv2.imshow('Video', canvas)
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+def eye_aspect_ratio(eye):
+
+	A = dist.euclidean(eye[1], eye[5])
+	B = dist.euclidean(eye[2], eye[4])
+
+
+	C = dist.euclidean(eye[0], eye[3])
+
+
+	ear = (A + B) / (2.0 * C)
+
+
+	return ear
+ 
+
+ap = argparse.ArgumentParser()
+ap.add_argument("-p", "--shape-predictor",default="shape_predictor_68_face_landmarks.dat",
+	help="path to facial landmark predictor")
+ap.add_argument("-v", "--video", type=str, default="camera",
+	help="path to input video file")
+ap.add_argument("-t", "--threshold", type = float, default=0.27,
+	help="threshold to determine closed eyes")
+ap.add_argument("-f", "--frames", type = int, default=2,
+	help="the number of consecutive frames the eye must be below the threshold")
+
+def main() :
+    args = vars(ap.parse_args())
+    EYE_AR_THRESH = args['threshold']
+    EYE_AR_CONSEC_FRAMES = args['frames']
+
+
+    COUNTER = 0
+    TOTAL = 0
+
+
+    print("[INFO] loading cascade code loading")
+    detector = dlib.get_frontal_face_detector()
+    predictor = dlib.shape_predictor(args["shape_predictor"])
+ 
+
+    (lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
+    (rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
+    
+
+
+    if args['video'] == "camera":
+        vs = VideoStream(src=0).start()
+        fileStream = False
+    else:
+        vs = FileVideoStream(args["video"]).start()
+        fileStream = True
+   
+    time.sleep(1.0)
+    
+
+    while True:
+
+    	if fileStream and not vs.more():
+    		break
+
+    	frame = vs.read()
+    	frame = imutils.resize(frame, width=450)
+    	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    	rects = detector(gray, 0)
+    
+
+    	for rect in rects:
+
+    		shape = predictor(gray, rect)
+    		shape = face_utils.shape_to_np(shape)
+
+
+    		leftEye = shape[lStart:lEnd]
+    		rightEye = shape[rStart:rEnd]
+    		leftEAR = eye_aspect_ratio(leftEye)
+    		rightEAR = eye_aspect_ratio(rightEye)
+
+    		ear = (leftEAR + rightEAR) / 2.0
+    
+
+    		leftEyeHull = cv2.convexHull(leftEye)
+    		rightEyeHull = cv2.convexHull(rightEye)
+    		cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
+    		cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)
+
+    		if ear < EYE_AR_THRESH:
+    			COUNTER += 1
+    
+
+    		else:
+
+    			if COUNTER >= EYE_AR_CONSEC_FRAMES:
+    				TOTAL += 1
+    
+
+    			COUNTER = 0
+    
+
+    		#cv2.putText(frame, "pregnent eye : {}".format(TOTAL), (10, 30),
+    			#cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+
+    		cv2.putText(frame, "prgnent eye skin beat: {}".format(ear), (30, 30),
+    			cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
+     
+
+    	cv2.imshow("Frame", frame)
+    	key = cv2.waitKey(1) & 0xFF
+     
+
+    	if key == ord("q"):
+    		break
+    
+    # do a bit of cleanup
+    cv2.destroyAllWindows()
+    vs.stop()
+if __name__ == '__main__' :
+    main()