def test2():
images = ['imgs/1.jpg', 'imgs/2.jpg']
style_path = 'styles/var'
styles = os.listdir(style_path)
target, sess, content, y1, y2, y3, y4, alpha1, alpha2, alpha3 = Init(
args.C_NUMS, args.PATH_MODEL)
x_len = args.C_NUMS + 1
y_len = len(images) + 1
img_all = Image.new("RGB", (x_len * 512, y_len * 512))
for i, style_name in enumerate(styles):
path = os.path.join(style_path, style_name)
with Image.open(path) as img:
img_resized = center_crop_img(img).resize((512, 512))
img_all.paste(img_resized, get_point(0, i + 1, 512))
for content_n in range(y_len - 1):
with Image.open(images[content_n]) as img:
img_resized = center_crop_img(img).resize((512, 512))
img_all.paste(img_resized, get_point(content_n + 1, 0, 512))
for style_n in range(x_len - 1):
img_arr = np.array(img)
y = np.zeros([1, 10])
y[0, style_n] = 1
img_stylized_arr = sess.run(target,
feed_dict={
content:
img_arr[np.newaxis, :, :, :],
y1:
y,
y2:
None,
y3:
None,
y4:
None,
alpha1:
1,
alpha2:
None,
alpha3:
None
})
img_stylized = Image.fromarray(
np.uint8(img_stylized_arr[0, :, :, :]))
img_stylized.save('{}_{}'.format(
style_n,
os.path.split(images[content_n])[1]))
img_stylized = center_crop_img(img_stylized).resize((512, 512))
img_all.paste(img_stylized,
get_point(content_n + 1, style_n + 1, 512))
def save_25result(self):
size = 5
i = 0
# 按行生成
while i < size:
# 1、2风格权重之和
x_sum = 100 - i * 25.0
# 3、4风格权重之和
y_sum = i * 25
# 1、2风格之和进行五等分，计算权重step值
x_step = x_sum / 4.0
# 3、4风格之和进行五等分，计算权重step值
y_step = y_sum / 4.0
# 按列生成
j = 0
while j < size:
# 计算1、2风格的权重
ap1 = x_sum - j * x_step
ap2 = j * x_step
# 计算3风格权重
ap3 = y_sum - j * y_step
# 归一化后存到args中
alphas = (float('%.2f' % (ap1 / 100.0)),
float('%.2f' % (ap2 / 100.0)),
float('%.2f' % (ap3 / 100.0)))
# 返回融合后图像
# img_return = stylize(args.PATH_IMG, args.PATH_RESULTS, args.LABEL_1, args.LABEL_2, args.LABEL_3,
# args.LABEL_4, args.ALPHA1, args.ALPHA2, args.ALPHA3, target, sess, content, y1, y2, y3,
# y4, alpha1, alpha2, alpha3)
img_return = self.stylize(alphas)
# array转IMG
img_return = Image.fromarray(np.uint8(img_return[0, :, :, :]))
# 将5个图像按行拼接
if j == 0:
width, height = img_return.size
img_5 = Image.new(img_return.mode, (width * 5, height))
img_5.paste(img_return,
(width * j, 0, width * (j + 1), height))
j = j + 1
# 将多个行拼接图像，拼接成5*5矩阵
if i == 0:
img_25 = Image.new(img_return.mode, (width * 5, height * 5))
img_25.paste(img_5, (0, height * i, width * 5, height * (i + 1)))
i = i + 1
# 将5*5矩阵图像的4个角加上4个风格图像，以作对比
img_25_4 = Image.new(img_return.mode, (width * 7, height * 5))
img_25_4 = ImageOps.invert(img_25_4)
img_25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[0] + 1) + '.png')).resize(
(width, height)), (0, 0, width, height))
img_25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[1] + 1) + '.png')).resize(
(width, height)),
(width * 6, 0, width * 7, height))
img_25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[2] + 1) + '.png')).resize(
(width, height)),
(0, height * 4, width, height * 5))
img_25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[3] + 1) + '.png')).resize(
(width, height)),
(width * 6, height * 4, width * 7, height * 5))
img_25_4.paste(img_25, [width, 0, width * 6, height * 5])
# 存储5*5图像矩阵
img_25.save(self.stylizer_arg.PATH_RESULTS +
self.img_path.split('/')[-1].split('.')[0] +
str(self.label_list) + '_result_25' + '.jpg')
# 存储5*5+4风格图像矩阵
print(self.stylizer_arg.PATH_RESULTS +
self.img_path.split('/')[-1].split('.')[0] +
str(self.label_list) + '_result_25_4' + '.jpg' + " saved!")
def generate_result(self):
size = 5
i = 0
# 按行生成
while i < size:
# 1、2风格权重之和
x_sum = 100 - i * 25.0
# 3、4风格权重之和
y_sum = i * 25
# 1、2风格之和进行五等分，计算权重step值
x_step = x_sum / 4.0
# 3、4风格之和进行五等分，计算权重step值
y_step = y_sum / 4.0
# 按列生成
j = 0
while j < size:
# 计算1、2风格的权重
ap1 = x_sum - j * x_step
ap2 = j * x_step
# 计算3风格权重
ap3 = y_sum - j * y_step
ap4 = j * y_step
# 归一化后存到alphas中
alphas = (float('%.2f' % (ap1 / 100.0)),
float('%.2f' % (ap2 / 100.0)),
float('%.2f' % (ap3 / 100.0)),
float('%.2f' % (ap4 / 100.0)))
# 返回融合后图像
img_return = self.stylize(alphas)
# array转IMG
img_return = Image.fromarray(np.uint8(img_return[0, :, :, :]))
# 将5个图像按行拼接
if j == 0:
width, height = img_return.size
img_5 = Image.new(img_return.mode, (width * 5, height))
img_5.paste(img_return,
(width * j, 0, width * (j + 1), height))
j = j + 1
# 将多个行拼接图像，拼接成5*5矩阵
if i == 0:
img_25 = Image.new(img_return.mode, (width * 5, height * 5))
img_25.paste(img_5, (0, height * i, width * 5, height * (i + 1)))
i = i + 1
# 将5*5矩阵图像的4个角加上4个风格图像，以作对比
img25_4 = Image.new(img_25.mode, (width * 7, height * 5))
img25_4 = ImageOps.invert(img25_4)
img25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[0] + 1) + '.png')).resize(
(width, height)), (0, 0, width, height))
img25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[1] + 1) + '.png')).resize(
(width, height)),
(width * 6, 0, width * 7, height))
img25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[2] + 1) + '.png')).resize(
(width, height)),
(0, height * 4, width, height * 5))
img25_4.paste(
center_crop_img(
Image.open(self.stylizer_arg.PATH_STYLE +
str(self.label_list[3] + 1) + '.png')).resize(
(width, height)),
(width * 6, height * 4, width * 7, height * 5))
img25_4.paste(img_25, [width, 0, width * 6, height * 5])
self.img25 = img_25
self.img25_4 = img25_4