Python：基于深度学习的图像分割后修改图片颜色（以VOC2012数据集为例）

用深度学习算法对图像进行分割任务后，得到的分割图像中的物体往往是各种不同深浅的灰色，不容易看清楚各物体的界限。以VOC2012为例，可以使用以下程序对分割后输出的图像批量修改颜色。

import os
from PIL import Image
import time
from tqdm import tqdm# 源目录
MyPath = 'D:\code\ChangeColor\sem_seg/'
# 输出目录
OutPath = 'D:\code\ChangeColor\sem_seg_out/'def processImage(filesoure, destsoure, name, imgtype):'''filesoure是存放待转换图片的目录destsoure是存在输出转换后图片的目录name是文件名imgtype是文件类型'''imgtype = 'bmp' if imgtype == '.bmp' else 'png'# 打开图片im = Image.open(filesoure + name)img = im.convert("RGBA")pixdata = img.load()# 二值化for y in range(img.size[1]):for x in range(img.size[0]):if pixdata[x, y][0] ==1:pixdata[x, y] = (128,0,0, 255)if pixdata[x, y][0] ==2:pixdata[x, y] = (0,128,0, 255)if pixdata[x, y][0] ==3:pixdata[x, y] = (128,128,0, 255)if pixdata[x, y][0] ==4:pixdata[x, y] = (0, 0, 128, 255)if pixdata[x, y][0] ==5:pixdata[x, y] = (128,0,128, 255)if pixdata[x, y][0] ==6:pixdata[x, y] = (0,128,128, 255)if pixdata[x, y][0] ==7:pixdata[x, y] = (128,128,128, 255)if pixdata[x, y][0] ==8:pixdata[x, y] = (64,0,0, 255)if pixdata[x, y][0] ==9:pixdata[x, y] = (192,0,0, 255)if pixdata[x, y][0] ==10:pixdata[x, y] = (64,128,0, 255)if pixdata[x, y][0] ==11:pixdata[x, y] = (192,128,0, 255)if pixdata[x, y][0] ==12:pixdata[x, y] = (64,0,128, 255)if pixdata[x, y][0] ==13:pixdata[x, y] = (192,0,128, 255)if pixdata[x, y][0] ==14:pixdata[x, y] = (64,128,128, 255)if pixdata[x, y][0] ==15:pixdata[x, y] = (192,128,128, 255)if pixdata[x, y][0] ==16:pixdata[x, y] = (0,64,0, 255)if pixdata[x, y][0] ==17:pixdata[x, y] = (128,64,0, 255)if pixdata[x, y][0] ==18:pixdata[x, y] = (0,192,0, 255)if pixdata[x, y][0] ==19:pixdata[x, y] = (128,192,0, 255)if pixdata[x, y][0] ==20:pixdata[x, y] = (0,64,128, 255)# for y in range(img.size[1]):#     for x in range(img.size[0]):#         if pixdata[x, y][1] !=0:#             pixdata[x, y] = (255, 255, 255, 255)## for y in range(img.size[1]):#     for x in range(img.size[0]):#         if pixdata[x, y][2] != 0:#             pixdata[x, y] = (255, 255, 255, 255)img.save(destsoure + name, imgtype)def run():# 切换到源目录，遍历源目录下所有图片os.chdir(MyPath)for i in tqdm(os.listdir(os.getcwd())):# 检查后缀postfix = os.path.splitext(i)[1]if postfix == '.bmp' or postfix == '.png':processImage(MyPath, OutPath, i, postfix)time.sleep(0.01)if __name__ == '__main__':run()

修改后的分割图像如图所示：