def load_image_points(path, size):
print 'in load image points'
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
print 'No face in %s' % path
return None, None
else:
# print 'Face landmark points : ',points
# for i in range (0,71):
# cv2.line(img, (points[i][0],points[i][1]), (points[i][0],points[i][1]), (0,255,0),5)
# cv2.imshow('original points',img)
# cv2.waitKey(0)
cv2.line(img, (points[18][0],points[18][1]), (points[18][0],points[18][1]), (255,224,0),5)
cv2.line(img, (points[21][0],points[21][1]), (points[21][0],points[21][1]), (255,224,0),5)
cv2.line(img, (points[22][0],points[22][1]), (points[22][0],points[22][1]), (255,224,0),5)
cv2.line(img, (points[25][0],points[25][1]), (points[25][0],points[25][1]), (255,224,0),5)
cv2.line(img, (points[30][0],points[30][1]), (points[30][0],points[30][1]), (255,0,0),5)
cv2.line(img, (points[40][0],points[40][1]), (points[40][0],points[40][1]), (255,0,0),5)
cv2.line(img, (points[54][0],points[54][1]), (points[54][0],points[54][1]), (0,255,0),5)
cv2.line(img, (points[56][0],points[56][1]), (points[56][0],points[56][1]), (0,255,0),5)
cv2.line(img, (points[58][0],points[58][1]), (points[58][0],points[58][1]), (0,255,0),5)
cv2.line(img, (points[59][0],points[59][1]), (points[59][0],points[59][1]), (0,0,255),5)
cv2.line(img, (points[65][0],points[65][1]), (points[65][0],points[65][1]), (0,0,255),5)
cv2.imshow("img",img)
cv2.waitKey(0)
return aligner.resize_align(img, points, size)
def load_image_points(path, size):
# print 'in load image points'
# img = scipy.ndimage.imread(path)[..., :3]
img = cv2.imread(path)[..., :3]
# print 'in load image points'
# img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
print 'No face in %s' % path
return None, None
else:
# print 'Face landmark points : ',points
# for i in range (0,71):
# cv2.line(img, (points[i][0],points[i][1]), (points[i][0],points[i][1]), (0,255,0),5)
# cv2.imshow('original points',img)
# cv2.waitKey(0)
# cv2.line(img, (points[18][0],points[18][1]), (points[18][0],points[18][1]), (255,224,0),5)
# cv2.line(img, (points[21][0],points[21][1]), (points[21][0],points[21][1]), (255,224,0),5)
# cv2.line(img, (points[22][0],points[22][1]), (points[22][0],points[22][1]), (255,224,0),5)
# cv2.line(img, (points[25][0],points[25][1]), (points[25][0],points[25][1]), (255,224,0),5)
#
# cv2.line(img, (points[30][0],points[30][1]), (points[30][0],points[30][1]), (255,0,0),5)
# cv2.line(img, (points[40][0],points[40][1]), (points[40][0],points[40][1]), (255,0,0),5)
#
# cv2.line(img, (points[54][0],points[54][1]), (points[54][0],points[54][1]), (0,255,0),5)
# cv2.line(img, (points[56][0],points[56][1]), (points[56][0],points[56][1]), (0,255,0),5)
# cv2.line(img, (points[58][0],points[58][1]), (points[58][0],points[58][1]), (0,255,0),5)
#
# cv2.line(img, (points[59][0],points[59][1]), (points[59][0],points[59][1]), (0,0,255),5)
# cv2.line(img, (points[65][0],points[65][1]), (points[65][0],points[65][1]), (0,0,255),5)
# cv2.imshow("img",img)
# cv2.waitKey(0)
# return aligner.resize_align(img, points, size)
return aligner.resize_align(img, points, size)
def load_image_points(path, size):
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
return None, None
else:
return aligner.resize_align(img, points, size)
def load_image_points(path, size):
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
if len(points) == 0:
return None, None
else:
return aligner.resize_align(img, points, size)
def load_image_points(path, size):
img = cv2.imread(path)
points = locator.face_points(img)
if len(points) == 0:
print('No face in %s' % path)
return None, None
else:
return aligner.resize_align(img, points, size)
def test_local():
from functools import partial
import cv2
import scipy.misc
import locator
import aligner
from matplotlib import pyplot as plt
# Load source image
face_points_func = partial(locator.face_points, '../data')
base_path = '../females/Screenshot 2015-03-04 17.11.12.png'
src_path = '../females/BlDmB5QCYAAY8iw.jpg'
src_img = cv2.imread(src_path)
# Define control points for warps
src_points = face_points_func(src_path)
base_img = cv2.imread(base_path)
base_points = face_points_func(base_path)
size = (600, 500)
src_img, src_points = aligner.resize_align(src_img, src_points, size)
base_img, base_points = aligner.resize_align(base_img, base_points, size)
result_points = locator.weighted_average_points(src_points, base_points,
0.2)
# Perform transform
dst_img1 = warp_image(src_img, src_points, result_points, size)
dst_img2 = warp_image(base_img, base_points, result_points, size)
import blender
ave = blender.weighted_average(dst_img1, dst_img2, 0.6)
mask = blender.mask_from_points(size, result_points)
blended_img = blender.poisson_blend(dst_img1, dst_img2, mask)
plt.subplot(2, 2, 1)
plt.imshow(ave)
plt.subplot(2, 2, 2)
plt.imshow(dst_img1)
plt.subplot(2, 2, 3)
plt.imshow(dst_img2)
plt.subplot(2, 2, 4)
plt.imshow(blended_img)
plt.show()
def test_local(): from functools import partial import scipy.ndimage import scipy.misc import locator import aligner from matplotlib import pyplot as plt # Load source image face_points_func = partial(locator.face_points, '../data') base_path = '../females/Screenshot 2015-03-04 17.11.12.png' src_path = '../females/BlDmB5QCYAAY8iw.jpg' src_img = scipy.ndimage.imread(src_path)[:, :, :3] # Define control points for warps src_points = face_points_func(src_path) base_img = scipy.ndimage.imread(base_path)[:, :, :3] base_points = face_points_func(base_path) size = (600, 500) src_img, src_points = aligner.resize_align(src_img, src_points, size) base_img, base_points = aligner.resize_align(base_img, base_points, size) result_points = locator.weighted_average_points(src_points, base_points, 0.2) # Perform transform dst_img1 = warp_image(src_img, src_points, result_points, size) dst_img2 = warp_image(base_img, base_points, result_points, size) print 'blending' import blender ave = blender.weighted_average(dst_img1, dst_img2, 0.6) mask = blender.mask_from_points(size, result_points) blended_img = blender.poisson_blend(dst_img1, dst_img2, mask) plt.subplot(2, 2, 1) plt.imshow(ave) plt.subplot(2, 2, 2) plt.imshow(dst_img1) plt.subplot(2, 2, 3) plt.imshow(dst_img2) plt.subplot(2, 2, 4) plt.imshow(blended_img) plt.show()
def load_image_points(path, size):
img = scipy.ndimage.imread(path)[..., :3]
points = locator.face_points(path)
## Add image boundary points
#x,y = np.meshgrid([0,size[0]/2,size[0]],[0,size[1]/2,size[1]])
#im_edge_points = np.vstack((y.flatten(),x.flatten())).T
#points = np.vstack((points,im_edge_points))
if len(points) == 0:
print('No face in %s' % path)
return None, None
else:
return aligner.resize_align(img, points, size)
def load_image_points(path, size, fromDb=False):
img = scipy.ndimage.imread(path)[..., :3]
if fromDb:
with con:
cur = con.cursor()
data = cur.execute("SELECT points FROM entries WHERE name=?", ([os.path.basename(path)]))
points = convert_array(cur.fetchone()[0])
else:
points = locator.face_points(path)
if len(points) == 0:
return None, None
else:
return aligner.resize_align(img, points, size)