import matplotlib.pyplot as plt
import PIL.Image as Image
import os
import cv2
import numpy
from torchvision import transforms
unloader =transforms.ToPILImage()
IMAGES_PATH = '/home/dushuai/word/superpixel_fcn-master/save_out/'
IMAGES_FORMAT = ['.jpg', '.JPG']
IMAGE_SIZE = 160
IMAGE_ROW = 2
IMAGE_COLUMN = 3
IMAGE_SAVE_PATH = '/home/dushuai/word/superpixel_fcn-master/save_out/final.jpg'
image_names = [name for name in os.listdir(IMAGES_PATH) for item in IMAGES_FORMAT if
os.path.splitext(name)[1] == item]
image_names = sorted(image_names)
print(image_names)
if len(image_names) != IMAGE_ROW * IMAGE_COLUMN:
raise ValueError("合成图片的参数和要求的数量不能匹配!")
def image_compose():
to_image = Image.new('RGB', (IMAGE_COLUMN * IMAGE_SIZE, IMAGE_ROW * IMAGE_SIZE))
print('新画布的大小:{} + type:{}'.format(to_image.size,type(to_image)))
for y in range(1, IMAGE_ROW + 1):
for x in range(1, IMAGE_COLUMN + 1):
for i in range(0,6,1):
from_image = Image.open(IMAGES_PATH + image_names[IMAGE_COLUMN * (y - 1) + x - 1])
to_image.paste(from_image, ((x - 1) * IMAGE_SIZE, (y - 1) * IMAGE_SIZE))
return to_image.save(IMAGE_SAVE_PATH)
if __name__ == '__main__':
image_compose()