python换脸融合实例代码
代码语言:python
所属分类:人工智能
代码描述:python换脸融合代码,可直接在bfwstuio中运行和编辑
下面为部分代码预览,完整代码请点击下载或在bfwstudio webide中打开
import cv2 import dlib import numpy import sys PREDICTOR_PATH = "/data/wwwroot/default/model/shape_predictor_68_face_landmarks.dat" SCALE_FACTOR = 1 FEATHER_AMOUNT = 11 FACE_POINTS = list(range(17, 68)) MOUTH_POINTS = list(range(48, 61)) RIGHT_BROW_POINTS = list(range(17, 22)) LEFT_BROW_POINTS = list(range(22, 27)) RIGHT_EYE_POINTS = list(range(36, 42)) LEFT_EYE_POINTS = list(range(42, 48)) NOSE_POINTS = list(range(27, 35)) JAW_POINTS = list(range(0, 17)) # Points used to line up the images. ALIGN_POINTS = (LEFT_BROW_POINTS + RIGHT_EYE_POINTS + LEFT_EYE_POINTS + RIGHT_BROW_POINTS + NOSE_POINTS + MOUTH_POINTS) # Points from the second image to overlay on the first. The convex hull of each # element will be overlaid. OVERLAY_POINTS = [ LEFT_EYE_POINTS + RIGHT_EYE_POINTS + LEFT_BROW_POINTS + RIGHT_BROW_POINTS, NOSE_POINTS + MOUTH_POINTS, ] # Amount of blur to use during colour correction, as a fraction of the # pupillary distance. COLOUR_CORRECT_BLUR_FRAC = 0.6 detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor(PREDICTOR_PATH) class TooManyFaces(Exception): pass class NoFaces(Exception): pass def get_landmarks(im): rects = detector(im, 1) if len(rects) > 1: raise TooManyFaces if len(rects) == 0: raise NoFaces return numpy.matrix([[p.x, p.y] for p in predictor(im, rects[0]).parts()]) def annotate_landmarks(im, landmarks): im = im.copy() for idx, point in enumerate(landmarks): pos = (point[0, 0], point[0, 1]) cv2.putText(im, str(idx), pos, fontFace=cv2.FONT_HERSHEY_SCRIPT_SIMPLEX, fontScale=0.4, color=(0, 0, 255)) cv2.circle(im, pos, 3, color=(0, 255, 255)) return im def draw_convex_hull(im, points, color): points = cv2.convexHull(points) cv2.fillConvexPoly(im, points, color=color) def get_face_mask(im, landmarks): im = numpy.zeros(im.shape[:2], dtype=numpy.float64) for group in OVERLAY_POINTS: draw_convex_hull(im, landmarks[group], color=1) im = numpy.array([im, im, im]).transpose((1, 2, 0)) im = (cv2.GaussianBlur(im, (FEATHER_AMOUNT, FEATHER_AMOUNT), 0) > 0) * 1.0 im = cv2.GaussianBlur(im, (FEATHER_AMOUNT, FEATHER_AMOUNT), 0) return im def transformation_from_points(points1, points2): """ Return an affine transformation [s * R | T] such that: sum ||s*R*p1,i + T - p2,i||^2 is minimized. """ # Solve the procrustes problem by subtracting centroids, scaling by the # standard deviation, and then using the SVD to calculate the rotation. See # the following for more details: # https://en.wikipedia.org/wiki/Orthogonal_Procrustes_problem points1 = points1.astype(numpy.float64) points2 = points2.astype(numpy.float64) c1 = numpy.mean(points1, axis=0) c2 = numpy.me.........完整代码请登录后点击上方下载按钮下载查看
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