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Editing: app.py
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import cv2 import sys import os imagePath = sys.argv[1] imstr = os.path.splitext(imagePath)[0] image = cv2.imread(imagePath) gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) faceCascade = cv2.CascadeClassifier(cv2.data.haarcascades + "haarcascade_frontalface_default.xml") faces = faceCascade.detectMultiScale( gray, scaleFactor=1.0, minNeighbors=3, minSize=(35, 45) ) print("[INFO] Found {0} Faces.".format(len(faces))) for (x, y, w, h) in faces: cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2) roi_color = image[y:y + h, x:x + w] print("[INFO] Object found. Saving locally.") #cv2.imwrite(str(w) + str(h) + '_faces.jpg', roi_color) cv2.imwrite(imstr + '_faces.jpg', roi_color) status = cv2.imwrite('faces_detected.jpg', image) print("[INFO] Image faces_detected.jpg written to filesystem: ", status) #os.path.splitext(img)[0] #source: https://www.digitalocean.com/community/tutorials/how-to-detect-and-extract-faces-from-an-image-with-opencv-and-python