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GANimation/utils/face_utils.py

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+import face_recognition
+import cv2
+import numpy as np
+import skimage
+import skimage.transform
+import warnings
+
+def detect_faces(img):
+    '''
+    Detect faces in image
+    :param img: cv::mat HxWx3 RGB
+    :return: yield 4 <x,y,w,h>
+    '''
+    # detect faces
+    bbs = face_recognition.face_locations(img)
+
+    for y, right, bottom, x in bbs:
+        # Scale back up face bb
+        yield x, y, (right - x), (bottom - y)
+
+def detect_biggest_face(img):
+    '''
+    Detect biggest face in image
+    :param img: cv::mat HxWx3 RGB
+    :return: 4 <x,y,w,h>
+    '''
+    # detect faces
+    bbs = face_recognition.face_locations(img)
+
+    max_area = float('-inf')
+    max_area_i = 0
+    for i, (y, right, bottom, x) in enumerate(bbs):
+        area = (right - x) * (bottom - y)
+        if max_area < area:
+            max_area = area
+            max_area_i = i
+
+    if max_area != float('-inf'):
+        y, right, bottom, x = bbs[max_area_i]
+        return x, y, (right - x), (bottom - y)
+
+    return None
+
+def crop_face_with_bb(img, bb):
+    '''
+    Crop face in image given bb
+    :param img: cv::mat HxWx3
+    :param bb: 4 (<x,y,w,h>)
+    :return: HxWx3
+    '''
+    x, y, w, h = bb
+    return img[y:y+h, x:x+w, :]
+
+def place_face(img, face, bb):
+    x, y, w, h = bb
+    face = resize_face(face, size=(w, h))
+    img[y:y+h, x:x+w] = face
+    return img
+
+def resize_face(face_img, size=(128, 128)):
+    '''
+    Resize face to a given size
+    :param face_img: cv::mat HxWx3
+    :param size: new H and W (size x size). 128 by default.
+    :return: cv::mat size x size x 3
+    '''
+    return cv2.resize(face_img, size)
+
+def detect_landmarks(face_img):
+    landmakrs = face_recognition.face_landmarks(face_img)
+    return landmakrs[0] if len(landmakrs) > 0 else None