Mtcnn face-extractor for head extraction-CodePudding

I'm using Mtcnn network (https://towardsdatascience.com/face-detection-using-mtcnn-a-guide-for-face-extraction-with-a-focus-on-speed-c6d59f82d49) to detect faces and heads. For this I'm using the classical lines code for face detection :I get the coordinate of the top-left corner of the bouding-box of the face (x,y) the height and width of the box (h,w), then I expand the box to get the head in my crop :

import mtcnn
img = cv2.imread('images/' path_res)
faces = detector.detect_faces(img)# result
for result in faces:
    x, y, w, h = result['box']
    x1, y1 = x   w, y   h
x, y, w, h = result['box']
x1, y1 = x   w, y   h

if x-100>=0:
    a=x-100
else:
    a=0

if y-150 >=0:
    b=y-150
else:
    b=0

if x1 100 >= w:
    c=x1 100
else:
    c=w

if y1 60 >= h:
    d=y1 60
else:
    d=h

crop=img[b:d,a:c] #<--- final crop of the head

the problem is this solution works for some images, but for many anothers, in my crop, I get the shoulders and the neck of the target person. I think, it's because, the pixels/inch in each image (i.e. 150pixels in one image isn't the same in another image). Hence, what can I do to extract the head properly ? Many thanks

CodePudding user response：

You can use relative instead of absolute sizes for the margins around the detected faces. For example, 50% on top, bottom, left and right:

import mtcnn

img = cv2.imread('images/' path_res)

faces = []
for result in detector.detect_faces(img):
    x, y, w, h = result['box']

    b = max(0, y - (h//2))
    d = min(img.shape[0], (y h)   (h//2))
    a = max(0, x - (w//2):(x w))
    c = min(img.shape[1], (x w)   (w//2))
    
    face = img[b:d, a:c, :]
    faces.append(face)