110 lines
3.3 KiB
Python
110 lines
3.3 KiB
Python
#!/usr/bin/python3
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################################################################################
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# Authors: Fred (support@qo-op.com) + Mark
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# Version: 0.1
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# License: AGPL-3.0 (https://choosealicense.com/licenses/agpl-3.0/)
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################################################################################
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import cv2
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import os
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import time
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import subprocess
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import numpy as np
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cascPath = "./haarcascade_frontalface_default.xml"
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shot_images_path = "./tmp/"
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processed_images_path = "./processed_images"
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#if directories dont exist, make them
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if not os.path.isdir(shot_images_path):
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os.mkdir(shot_images_path)
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if not os.path.isdir(processed_images_path):
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os.mkdir(processed_images_path)
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print("FaceDetect READY...")
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sleep_count = 20
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while 1:
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files = os.listdir(shot_images_path)
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if not files:
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time.sleep(0.1)
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if sleep_count ==20:
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#print("sleeping ...")
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sleep_count = 0
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sleep_count+=1
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else:
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for file in files:
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# Get user supplied values
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imagePath = os.path.join(shot_images_path,file)
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# Create the haar cascade
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faceCascade = cv2.CascadeClassifier(cascPath)
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# Read the image
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#may read while image is not finished loading thus this work-around
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try:
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image = cv2.imread(imagePath)
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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except Exception:
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print("Could not read image... Retrying...")
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break
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# Detect faces in the image
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faces = faceCascade.detectMultiScale(
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gray,
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#scaleFactor=1,
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minNeighbors=1,
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minSize=(30, 30),
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flags = cv2.CASCADE_SCALE_IMAGE#cv.CV_HAAR_SCALE_IMAGE
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)
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print("Found {0} face(s)!".format(len(faces)))
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#iterate through the found faces
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count = 0
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for (x, y, w, h) in faces:
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x1 = int(x - w*0.05)
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y1 = int(y - h*0.1)
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x2 = int(x + w*1.1)
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y2 = int(y + h*1.25)
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#check if 'face' is really a face...
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check_gray = gray[y1:y2,x1:x2]
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check = faceCascade.detectMultiScale(
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check_gray,
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#scaleFactor=1,
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minNeighbors=1,
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minSize=(30, 30),
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flags = cv2.CASCADE_SCALE_IMAGE
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)
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if len(faces)==1:
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#We found ONE face :D
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#reshape to print width and height and write to ./processed_images
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(img_h,img_w) = check_gray.shape
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fw = 384/img_w
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img_out = cv2.resize(check_gray,(0,0), fx = fw, fy = fw )
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#brighten up the image
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added_brightness = 10
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img_out = img_out +added_brightness
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img_out = np.where((255-img_out)<added_brightness, 255, img_out + added_brightness )
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file_name = "./processed_images/face.jpg"
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cv2.imwrite(file_name, img_out)
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count+=1
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os.remove(imagePath)
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