语义分割，将RGB三通道的lable转为单通道

由于模型的label为单通道的图，需要进行颜色转换，参考了

csdn_label2color2label: 语义分割，灰度图与彩色图的相互转换

进行修改

import numpy as np
import os
import cv2
import time


def color2gray(img_path, color_map):
    # 读取图片
    color_img = cv2.imread(img_path, cv2.IMREAD_UNCHANGED)
    # 计算时间
    t0 = time.time()
    gray_img = np.zeros(shape=(color_img.shape[0], color_img.shape[1]), dtype=np.uint8)
    for i in range(color_map.shape[0]):
        index = np.where(np.all(color_img == color_map[i], axis=-1))  # np.all true false
        gray_img[index] = i
    t1 = time.time()
    time_cost = round(t1 - t0, 3)
    print(f"color2label  cost time {time_cost}")
    # 保存图片
    dir, name = os.path.split(img_path)
    save_dir='./gray_label'
    if not os.path.exists(save_dir):
        os.mkdir(save_dir)
    save_path = os.path.join(save_dir, name)
    cv2.imwrite(save_path, gray_img)

if __name__ == '__main__':
    # 你的colormap
    cmap = np.array(
        [
            (0, 0, 0),
            (108, 64, 20),
            (255, 229, 204),
            (0, 102, 0),
            (0, 255, 0),
            (0, 153, 153),
            (0, 128, 255),
            (0, 0, 255),
            (255, 255, 0),
            (255, 0, 127),
            (64, 64, 64),
            (255, 128, 0),
            (255, 0, 0),
            (153, 76, 0),
            (102, 102, 0),
            (102, 0, 0),
            (0, 255, 128),
            (204, 153, 255),
            (102, 0, 204),
            (255, 153, 204),
            (0, 102, 102),
            (153, 204, 255),
            (102, 255, 255),
            (101, 101, 11),
            (114, 85, 47)
        ]
    )
    # 文件路径
    img_dir = './label/'
    if not os.path.exists(img_dir):
        os.mkdir(img_dir)
    for img in os.listdir(img_dir):
        if not img.endswith((".png", ".jpg")):
            continue
        img_path = os.path.join(img_dir, img)
        color2gray(img_path, color_map=cmap)

color_map为你的颜色映射，输入文件夹路径就可以使用了

效果为