def histeq(img):
rh, rw, rc = img.shape
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img2 = None
img2 = cv2.equalizeHist(gray)
cv2.imshow('img', gray)
cv2.imshow('img2', img2)
cv2.waitKey(10000)
cv2.destroyAllWindows()
def histeq(img):
rh, rw, rc = img.shape
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
img2 = None
img2 = cv2.equalizeHist(gray)
cv2.imshow('img', gray)
cv2.imshow('img2', img2)
cv2.waitKey(10000)
cv2.destroyAllWindows()
def sharpen(img):
rh, rw, rc = img.shape
img2 = np.zeros((rh, rw, 3), dtype=np.uint8);
kernel_size = 3
scale = 1
delta = 0
ddepth = cv2.CV_64F
img2 = cv2.convertScaleAbs(cv2.Laplacian(img,ddepth,ksize = kernel_size,scale = scale,delta = delta))
sharpened = cv2.addWeighted(img, 1, img2, -0.5, 0)
cv2.imshow('original img', img)
cv2.imshow('sharpened img', sharpened)
cv2.waitKey(5000)
cv2.destroyAllWindows()
def show_face_body(img):
xcrop_bias = 50
body_head_portion = 5
start = time.time()
rh, rw, rc = img.shape
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
if y+h*2 > rh:
continue
crop_img = img[y+h:y+h*body_head_portion, x-xcrop_bias:x+w+xcrop_bias]
cv2.rectangle(img, (x-xcrop_bias,y+h), (x+w+xcrop_bias, y+h*body_head_portion), (0, 255, 0), 2)
#cv2.imwrite(img_path+'/'+f+'_'+str(ct)+'.jpg', crop_img)
cv2.imshow('img',img)
cv2.waitKey(1000)
cv2.destroyAllWindows()
end = time.time()
print 'total time consumed: %d'%int(end - start)
def show_face_body(img):
xcrop_bias = 50
body_head_portion = 5
start = time.time()
rh, rw, rc = img.shape
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
if y + h * 2 > rh:
continue
crop_img = img[y + h:y + h * body_head_portion,
x - xcrop_bias:x + w + xcrop_bias]
cv2.rectangle(img, (x - xcrop_bias, y + h),
(x + w + xcrop_bias, y + h * body_head_portion),
(0, 255, 0), 2)
#cv2.imwrite(img_path+'/'+f+'_'+str(ct)+'.jpg', crop_img)
cv2.imshow('img', img)
cv2.waitKey(1000)
cv2.destroyAllWindows()
end = time.time()
print 'total time consumed: %d' % int(end - start)
print blurriness
return blurriness
def get_face_region(gray_frame):
results = []
faces = face_cascade.detectMultiScale(gray_frame, 1.3, 5)
for (x,y,w,h) in faces:
results.append((x,y,w,h))
return results
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Test blurriness')
parser.add_argument('image_path', metavar='image_path',
help='path of the image that is to be calculated')
args = parser.parse_args()
img = cv2.imread(args.image_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = get_face_region(gray)
for item in faces:
x = item[0]
y = item[1]
w = item[2]
h = item[3]
cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
blurriness = get_blurriness(gray[y:y+h, x:x+w])
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img,'Blurriness:' + str(blurriness),(x,y), font, 1,(255,255,255),2)
cv2.imshow('img',img)
cv2.waitKey(5000)
cv2.destroyAllWindows()
def get_face_region(gray_frame):
results = []
faces = face_cascade.detectMultiScale(gray_frame, 1.3, 5)
for (x, y, w, h) in faces:
results.append((x, y, w, h))
return results
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Test blurriness')
parser.add_argument('image_path',
metavar='image_path',
help='path of the image that is to be calculated')
args = parser.parse_args()
img = cv2.imread(args.image_path)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = get_face_region(gray)
for item in faces:
x = item[0]
y = item[1]
w = item[2]
h = item[3]
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
blurriness = get_blurriness(gray[y:y + h, x:x + w])
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img, 'Blurriness:' + str(blurriness), (x, y), font, 1,
(255, 255, 255), 2)
cv2.imshow('img', img)
cv2.waitKey(5000)
cv2.destroyAllWindows()
