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faces.py
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faces.py
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import numpy as np
import cv2
from imutils import paths
import imutils
import os
face_cascade = cv2.CascadeClassifier('/Users/marioag/Documents/GitHub/gehl-detect/ocv2/opencv/data/haarcascades/haarcascade_frontalface_alt2.xml')
eye_cascade = cv2.CascadeClassifier('/Users/marioag/Documents/GitHub/gehl-detect/ocv2/opencv/data/haarcascades/haarcascade_mcs_upperbody.xml')
image_dir = '/Users/marioag/Dropbox (Personal)/documents/mit-github-projects/gehl/Gehl/img'
i = 0
for imagePath in os.listdir(image_dir):
if imagePath.endswith(".jpg"):
print "processing image {}".format(i)
imagePath = os.path.join(image_dir, imagePath)
img = cv2.imread(imagePath)
# print img
img = imutils.resize(img, width=min(2500, img.shape[1]))
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
img = cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
roi_gray = gray[y:y + h, x:x + w]
roi_color = img[y:y + h, x:x + w]
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex, ey, ew, eh) in eyes:
cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
# cv2.imshow('img', img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
cv2.imwrite("/Users/marioag/Documents/GitHub/gehl-detect/out/faces/from_img2/image{}.png".format(i), img)
i +=1