def main(self, src, dst):
graph = Image.open(src)
resultjson = facep.detect(src)
if resultjson != -1:
land_mark = resultjson
# Operate area
size = graph.size
width = size[0]
height = size[1]
contour_left3 = int(land_mark['result'][0]['landmark']['contour_left3']['x'] * width / 100) / 2 * 2
left_eyebrow_upper_middle = int(land_mark['result'][0]['landmark']['left_eyebrow_upper_middle']['y'] * height / 100 * 0.97) / 2 * 2
contour_right3 = int(land_mark['result'][0]['landmark']['contour_right3']['x'] * width / 100) / 2 * 2
contour_right7 = int(land_mark['result'][0]['landmark']['contour_right7']['y'] * height / 100) / 2 * 2
box = (contour_left3, left_eyebrow_upper_middle, contour_right3, contour_right7)
self.graph = graph.crop(box)
self.size = self.graph.size
self.width = self.size[0]
self.height = self.size[1]
self.photometricDec = 10.0
self.spatialDecay = 1.0
self.gain_mu = (1.0 - self.spatialDecay) / (1.0 + self.spatialDecay)
self.rho = 1.0 + self.spatialDecay
self.c = -0.5/(self.photometricDec * self.photometricDec)
self.hv_graph = ny.double(ny.zeros([self.height, self.width, 3]))
self.vh_graph = ny.double(ny.zeros([self.height, self.width, 3]))
self.result = ny.double(ny.zeros([self.height, self.width, 3]))
self.graph = ny.double(self.graph)
for d in range(3):
self.hv_graph = self.graph[:, :, d]
self.vh_graph = self.graph[:, :, d]
self.beeps_hv()
self.beeps_vh()
for row in range(self.height):
for col in range(self.width):
self.result[row, col, d] = (self.vh_graph[row, col] + self.hv_graph[row, col]) / 2
self.result = self.result[0:self.height-2, 0:self.width-2, :]
self.result = Image.fromarray(ny.uint8(self.result)).convert('RGB')
box = (contour_left3, left_eyebrow_upper_middle, contour_right3-2, contour_right7-2)
graph.paste(self.result, box)
graph.save(dst)
return 0
else:
graph.save(dst)
return -1
def baozou(src, dst):
graph = Image.open(src)
resultjson = facep.detect(src)
if resultjson != -1:
land_mark = resultjson
# Operate area
size = graph.size
width = size[0]
height = size[1]
left_eyebrow_left_corner = int(land_mark['result'][0]['landmark']['left_eyebrow_left_corner']['x'] * width / 100) / 2 * 2
left_eyebrow_upper_middle = int(land_mark['result'][0]['landmark']['left_eyebrow_upper_middle']['y'] * height / 100 * 0.97) / 2 * 2
contour_right7x = int(land_mark['result'][0]['landmark']['contour_right7']['x'] * width / 100) / 2 * 2
contour_right7y = int(land_mark['result'][0]['landmark']['contour_right7']['y'] * height / 100) / 2 * 2
box = (left_eyebrow_left_corner, left_eyebrow_upper_middle, contour_right7x, contour_right7y)
result = graph.crop(box)
result = ny.array(result)
result = ny.matrix(0.3 * result[:, :, 1] + 0.59 * result[:, :, 2] + 0.11 * result[:, :, 2])
R = Image.fromarray(ny.uint8(result)).convert('RGB')
size = R.size
width = size[0]
height = size[1]
# npercent = 2
# average = 128
brightness = sum(sum(result).T) / width / height / 128 / 2.8
# result += brightness * 0.9
result /= brightness
# result = average + (result - average) * npercent
for x in range(height):
for y in range(width):
if result[x, y] > 220:
result[x, y] *= (result[x, y] * 2.0 / 255)
result[x, y] = max(0, min(255, result[x, y]))
result = Image.fromarray(ny.uint8(result))
template = Image.open('PhotoManager/Library/template.jpg')
temp = (width + height) * 2
template = template.resize([temp, temp])
per = 0.30
x1 = int(temp / 2 - width / 2) / 2 * 2
y1 = int(temp * per - height / 2) / 2 * 2
x2 = int(temp / 2 + width / 2) / 2 * 2
y2 = int(temp * per + height / 2) / 2 * 2
tbox = [x1, y1, x2, y2]
template.paste(result, tbox)
result = Image.fromarray(ny.uint8(template)).convert('RGB')
result.save(dst)
return 0
else:
graph.save(dst)
return -1
def enlarge(src, dst):
# -*- coding: utf-8 -*-
graph = Image.open(src)
resultjson = facep.detect(src)
if resultjson != -1:
land_mark = resultjson
# Operate area
size = graph.size
width = size[0]
height = size[1]
pIn = ny.array(graph)
ptemp = pIn
cenX = int(land_mark['result'][0]['landmark']['left_eye_bottom']['y'] *
height / 100)
cenY = int(land_mark['result'][0]['landmark']['left_eye_bottom']['x'] *
width / 100)
left_eye_left_corner = int(
land_mark['result'][0]['landmark']['left_eye_left_corner']['x'] *
width / 100)
left_eye_right_corner = int(
land_mark['result'][0]['landmark']['left_eye_right_corner']['x'] *
width / 100)
left_eye_top = int(
land_mark['result'][0]['landmark']['left_eye_top']['y'] * height /
100)
left_eye_bottom = int(
land_mark['result'][0]['landmark']['left_eye_bottom']['y'] *
height / 100)
R = left_eye_right_corner - left_eye_left_corner
# R = left_eye_bottom - left_eye_top
R *= 1.1
theta = math.pi
for k in range(3):
for x in range(1 - cenX, left_eye_bottom - cenX):
for y in range(1 - cenY, width - cenY):
disX = int(1.2 * x)
disY = int(1.2 * y)
dis = disX * disX + disY * disY
r = math.sqrt(dis)
if r <= R and dis != 0:
xx = 2 * R * disX * math.acos(
math.sqrt(R * R - dis) / R) / (theta * r) + cenX
yy = 2 * R * disY * math.acos(
math.sqrt(R * R - dis) / R) / (theta * r) + cenY
xx = ny.around(ny.array(xx))
yy = ny.around(ny.array(yy))
if width >= yy >= 1 and height >= xx >= 1:
ptemp[x + cenX, y + cenY, k] = pIn[xx, yy, k]
else:
ptemp[x + cenX, y + cenY, k] = pIn[x + cenX, y + cenY,
k]
pOut = ptemp
bias = height / 64
cenX = int(land_mark['result'][0]['landmark']['right_eye_bottom']['y']
* height / 100) + bias
cenY = int(
land_mark['result'][0]['landmark']['right_eye_bottom']['x'] *
width / 100)
right_eye_left_corner = int(
land_mark['result'][0]['landmark']['right_eye_left_corner']['x'] *
width / 100)
right_eye_right_corner = int(
land_mark['result'][0]['landmark']['right_eye_right_corner']['x'] *
width / 100)
right_eye_top = int(
land_mark['result'][0]['landmark']['right_eye_top']['y'] * height /
100)
right_eye_bottom = int(
land_mark['result'][0]['landmark']['right_eye_bottom']['y'] *
height / 100)
R = right_eye_right_corner - right_eye_left_corner
# R = left_eye_bottom - left_eye_top
R *= 1.1
for k in range(3):
for x in range(1 - cenX, right_eye_bottom + bias - cenX):
for y in range(1 - cenY, width - cenY):
disX = int(1.2 * x)
disY = int(1.2 * y)
dis = disX * disX + disY * disY
r = math.sqrt(dis)
if r <= R and dis != 0:
xx = 2 * R * disX * math.acos(
math.sqrt(R * R - dis) / R) / (theta * r) + cenX
yy = 2 * R * disY * math.acos(
math.sqrt(R * R - dis) / R) / (theta * r) + cenY
xx = ny.around(ny.array(xx))
yy = ny.around(ny.array(yy))
if width >= yy >= 1 and height >= xx >= 1:
pOut[x + cenX, y + cenY, k] = pIn[xx, yy, k]
else:
pOut[x + cenX, y + cenY, k] = pIn[x + cenX, y + cenY,
k]
result = Image.fromarray(ny.uint8(pOut)).convert('RGB')
result.save(dst)
return 0
else:
graph.save(dst)
return -1
def baozou(src, dst):
graph = Image.open(src)
resultjson = facep.detect(src)
if resultjson != -1:
land_mark = resultjson
# Operate area
size = graph.size
width = size[0]
height = size[1]
left_eyebrow_left_corner = int(
land_mark['result'][0]['landmark']['left_eyebrow_left_corner']['x']
* width / 100) / 2 * 2
left_eyebrow_upper_middle = int(
land_mark['result'][0]['landmark']['left_eyebrow_upper_middle']
['y'] * height / 100 * 0.97) / 2 * 2
contour_right7x = int(
land_mark['result'][0]['landmark']['contour_right7']['x'] * width /
100) / 2 * 2
contour_right7y = int(
land_mark['result'][0]['landmark']['contour_right7']['y'] *
height / 100) / 2 * 2
box = (left_eyebrow_left_corner, left_eyebrow_upper_middle,
contour_right7x, contour_right7y)
result = graph.crop(box)
result = ny.array(result)
result = ny.matrix(0.3 * result[:, :, 1] + 0.59 * result[:, :, 2] +
0.11 * result[:, :, 2])
R = Image.fromarray(ny.uint8(result)).convert('RGB')
size = R.size
width = size[0]
height = size[1]
# npercent = 2
# average = 128
brightness = sum(sum(result).T) / width / height / 128 / 2.8
# result += brightness * 0.9
result /= brightness
# result = average + (result - average) * npercent
for x in range(height):
for y in range(width):
if result[x, y] > 220:
result[x, y] *= (result[x, y] * 2.0 / 255)
result[x, y] = max(0, min(255, result[x, y]))
result = Image.fromarray(ny.uint8(result))
template = Image.open('PhotoManager/Library/template.jpg')
temp = (width + height) * 2
template = template.resize([temp, temp])
per = 0.30
x1 = int(temp / 2 - width / 2) / 2 * 2
y1 = int(temp * per - height / 2) / 2 * 2
x2 = int(temp / 2 + width / 2) / 2 * 2
y2 = int(temp * per + height / 2) / 2 * 2
tbox = [x1, y1, x2, y2]
template.paste(result, tbox)
result = Image.fromarray(ny.uint8(template)).convert('RGB')
result.save(dst)
return 0
else:
graph.save(dst)
return -1
def main(self, src, dst):
graph = Image.open(src)
resultjson = facep.detect(src)
if resultjson != -1:
land_mark = resultjson
# Operate area
size = graph.size
width = size[0]
height = size[1]
contour_left3 = int(
land_mark['result'][0]['landmark']['contour_left3']['x'] *
width / 100) / 2 * 2
left_eyebrow_upper_middle = int(
land_mark['result'][0]['landmark']['left_eyebrow_upper_middle']
['y'] * height / 100 * 0.97) / 2 * 2
contour_right3 = int(
land_mark['result'][0]['landmark']['contour_right3']['x'] *
width / 100) / 2 * 2
contour_right7 = int(
land_mark['result'][0]['landmark']['contour_right7']['y'] *
height / 100) / 2 * 2
box = (contour_left3, left_eyebrow_upper_middle, contour_right3,
contour_right7)
self.graph = graph.crop(box)
self.size = self.graph.size
self.width = self.size[0]
self.height = self.size[1]
self.photometricDec = 10.0
self.spatialDecay = 1.0
self.gain_mu = (1.0 - self.spatialDecay) / (1.0 +
self.spatialDecay)
self.rho = 1.0 + self.spatialDecay
self.c = -0.5 / (self.photometricDec * self.photometricDec)
self.hv_graph = ny.double(ny.zeros([self.height, self.width, 3]))
self.vh_graph = ny.double(ny.zeros([self.height, self.width, 3]))
self.result = ny.double(ny.zeros([self.height, self.width, 3]))
self.graph = ny.double(self.graph)
for d in range(3):
self.hv_graph = self.graph[:, :, d]
self.vh_graph = self.graph[:, :, d]
self.beeps_hv()
self.beeps_vh()
for row in range(self.height):
for col in range(self.width):
self.result[row, col,
d] = (self.vh_graph[row, col] +
self.hv_graph[row, col]) / 2
self.result = self.result[0:self.height - 2, 0:self.width - 2, :]
self.result = Image.fromarray(ny.uint8(self.result)).convert('RGB')
box = (contour_left3, left_eyebrow_upper_middle,
contour_right3 - 2, contour_right7 - 2)
graph.paste(self.result, box)
graph.save(dst)
return 0
else:
graph.save(dst)
return -1
def enlarge(src, dst):
# -*- coding: utf-8 -*-
graph = Image.open(src)
resultjson = facep.detect(src)
if resultjson != -1:
land_mark = resultjson
# Operate area
size = graph.size
width = size[0]
height = size[1]
pIn = ny.array(graph)
ptemp = pIn
cenX = int(land_mark['result'][0]['landmark']['left_eye_bottom']['y'] * height / 100)
cenY = int(land_mark['result'][0]['landmark']['left_eye_bottom']['x'] * width / 100)
left_eye_left_corner = int(land_mark['result'][0]['landmark']['left_eye_left_corner']['x'] * width / 100)
left_eye_right_corner = int(land_mark['result'][0]['landmark']['left_eye_right_corner']['x'] * width / 100)
left_eye_top = int(land_mark['result'][0]['landmark']['left_eye_top']['y'] * height / 100)
left_eye_bottom = int(land_mark['result'][0]['landmark']['left_eye_bottom']['y'] * height / 100)
R = left_eye_right_corner - left_eye_left_corner
# R = left_eye_bottom - left_eye_top
R *= 1.1
theta = math.pi
for k in range(3):
for x in range(1 - cenX, left_eye_bottom - cenX):
for y in range(1 - cenY, width - cenY):
disX = int(1.2 * x)
disY = int(1.2 * y)
dis = disX * disX + disY * disY
r = math.sqrt(dis)
if r <= R and dis != 0:
xx = 2 * R * disX * math.acos(math.sqrt(R * R - dis) / R) / (theta * r) + cenX
yy = 2 * R * disY * math.acos(math.sqrt(R * R - dis) / R) / (theta * r) + cenY
xx = ny.around(ny.array(xx))
yy = ny.around(ny.array(yy))
if width >= yy >= 1 and height >= xx >= 1:
ptemp[x + cenX, y + cenY, k] = pIn[xx, yy, k]
else:
ptemp[x + cenX, y + cenY, k] = pIn[x + cenX, y + cenY, k]
pOut = ptemp
bias = height / 64
cenX = int(land_mark['result'][0]['landmark']['right_eye_bottom']['y'] * height / 100) + bias
cenY = int(land_mark['result'][0]['landmark']['right_eye_bottom']['x'] * width / 100)
right_eye_left_corner = int(land_mark['result'][0]['landmark']['right_eye_left_corner']['x'] * width / 100)
right_eye_right_corner = int(land_mark['result'][0]['landmark']['right_eye_right_corner']['x'] * width / 100)
right_eye_top = int(land_mark['result'][0]['landmark']['right_eye_top']['y'] * height / 100)
right_eye_bottom = int(land_mark['result'][0]['landmark']['right_eye_bottom']['y'] * height / 100)
R = right_eye_right_corner - right_eye_left_corner
# R = left_eye_bottom - left_eye_top
R *= 1.1
for k in range(3):
for x in range(1 - cenX, right_eye_bottom + bias - cenX):
for y in range(1 - cenY, width - cenY):
disX = int(1.2 * x)
disY = int(1.2 * y)
dis = disX * disX + disY * disY
r = math.sqrt(dis)
if r <= R and dis != 0:
xx = 2 * R * disX * math.acos(math.sqrt(R * R - dis) / R) / (theta * r) + cenX
yy = 2 * R * disY * math.acos(math.sqrt(R * R - dis) / R) / (theta * r) + cenY
xx = ny.around(ny.array(xx))
yy = ny.around(ny.array(yy))
if width >= yy >= 1 and height >= xx >= 1:
pOut[x + cenX, y + cenY, k] = pIn[xx, yy, k]
else:
pOut[x + cenX, y + cenY, k] = pIn[x + cenX, y + cenY, k]
result = Image.fromarray(ny.uint8(pOut)).convert('RGB')
result.save(dst)
return 0
else:
graph.save(dst)
return -1
