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Run the code like this: | ||
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*python face_detect.py abba.png* | ||
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If you want to understand how the code works, the details are here: | ||
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https://realpython.com/blog/python/face-recognition-with-python/ | ||
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Update: Now supports OpenCV3. This change has been made by furetosan ( https://github.com/furetosan) and tested on Linux. | ||
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To run the OpenCV3 version, run facedetect_cv3.py. |
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import cv2 | ||
import sys | ||
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# Get user supplied values | ||
imagePath = sys.argv[1] | ||
cascPath = "haarcascade_frontalface_default.xml" | ||
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# Create the haar cascade | ||
faceCascade = cv2.CascadeClassifier(cascPath) | ||
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# Read the image | ||
image = cv2.imread(imagePath) | ||
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | ||
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# Detect faces in the image | ||
faces = faceCascade.detectMultiScale( | ||
gray, | ||
scaleFactor=1.1, | ||
minNeighbors=5, | ||
minSize=(30, 30), | ||
flags = cv2.cv.CV_HAAR_SCALE_IMAGE | ||
) | ||
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print("Found {0} faces!".format(len(faces))) | ||
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# Draw a rectangle around the faces | ||
for (x, y, w, h) in faces: | ||
cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2) | ||
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cv2.imshow("Faces found", image) | ||
cv2.waitKey(0) |
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import cv2 | ||
import sys | ||
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# Get user supplied values | ||
imagePath = sys.argv[1] | ||
cascPath = "haarcascade_frontalface_default.xml" | ||
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# Create the haar cascade | ||
faceCascade = cv2.CascadeClassifier(cascPath) | ||
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# Read the image | ||
image = cv2.imread(imagePath) | ||
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | ||
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# Detect faces in the image | ||
faces = faceCascade.detectMultiScale( | ||
gray, | ||
scaleFactor=1.1, | ||
minNeighbors=5, | ||
minSize=(30, 30) | ||
#flags = cv2.CV_HAAR_SCALE_IMAGE | ||
) | ||
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print("Found {0} faces!".format(len(faces))) | ||
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# Draw a rectangle around the faces | ||
for (x, y, w, h) in faces: | ||
cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2) | ||
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cv2.imshow("Faces found", image) | ||
cv2.waitKey(0) |
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