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Hi @DuinoDu , I need a Python version of the following matlab routine, which is provided by Yandong Wen to perform a 2-D face alignment using the 5 facial points obtained by MTCNN:

``````% load face image, and align to 112 X 96
imgSize = [112, 96];
coord5points = [30.2946, 65.5318, 48.0252, 33.5493, 62.7299; ...
51.6963, 51.5014, 71.7366, 92.3655, 92.2041];

facial5points = [105.8306, 147.9323, 121.3533, 106.1169, 144.3622; ...
109.8005, 112.5533, 139.1172, 155.6359, 156.3451];

Tfm =  cp2tform(facial5points', coord5points', 'similarity');
cropImg = imtransform(image, Tfm, 'XData', [1 imgSize(2)],...
'YData', [1 imgSize(1)], 'Size', imgSize);
``````

I have already tried some code with OpenCV and skimage, using the points obtained by your code; but no success:

``````import numpy as np
import cv2

imgSize = (112, 96)

# given a dimension size, calculate the center coordinate
calc_center_coord = lambda x: np.float32(x-1)/2 if x % 2 == 0 else np.float32((x-1)/2)

# calculate normalized coordinates
calc_norm_coord = lambda x,center,scale: (x-center)/scale

x_ = [30.2946, 65.5318, 48.0252, 33.5493, 62.7299]
y_ = [51.6963, 51.5014, 71.7366, 92.3655, 92.2041]
xc, yc = calc_center_coord(imgSize[1]), calc_center_coord(imgSize[0])
x_norm = [calc_norm_coord(x, xc, imgSize[1]) for x in x_]
y_norm = [calc_norm_coord(y, yc, imgSize[0]) for y in y_]

src = np.array( zip(x_norm,y_norm) ).astype(np.float32).reshape(1,5,2)

w, h = img.shape[1], img.shape[0]
img_c_x, img_c_y = calc_center_coord(img.shape[1]), calc_center_coord(img.shape[0])

# there might be more than one faces, hence
# multiple sets of points
for pset in points:
img2 = img.copy()

pset_x = pset[0:5]
pset_y = pset[5:10]

pset_norm_x = [calc_norm_coord(x,img_c_x,imgSize[1]) for x in pset_x]
pset_norm_y = [calc_norm_coord(y,img_c_y,imgSize[0]) for y in pset_y]

dst = np.array( zip(pset_norm_x,pset_norm_y) ).astype(np.float32).reshape(1,5,2)

transmat = cv2.estimateRigidTransform( src, dst, False )

out = cv2.warpAffine(img2, transmat, (w, h))

cv2.imshow("result", out)
cv2.waitKey(0)
``````

output looks totally wrong:

### Issue Analytics

• State:
• Created 6 years ago

7reactions
kizilkanatcommented, May 27, 2017

This worked fine:

``````import numpy as np
import cv2

imgSize = (112, 96)

x_ = [30.2946, 65.5318, 48.0252, 33.5493, 62.7299]
y_ = [51.6963, 51.5014, 71.7366, 92.3655, 92.2041]

src = np.array( zip(x_, y_) ).astype(np.float32).reshape(1,5,2)

alignedFaces = []

# there might be more than one faces, hence
# multiple sets of points
for pset in points:
img2 = img.copy()

pset_x = pset[0:5]
pset_y = pset[5:10]

dst = np.array( zip(pset_x, pset_y) ).astype(np.float32).reshape(1,5,2)

transmat = cv2.estimateRigidTransform( dst, src, False )

out = cv2.warpAffine(img2, transmat, (imgSize[1], imgSize[0]))

alignedFaces.append(out)
``````
2reactions
nttstarcommented, Sep 20, 2017

you can refer to my article: here

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