import os
import os.path as osp
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt

# 定义数据路径和文件后缀
data_root = 'data/LoveDA/Train/pv'
img_dir = 'images_png'
mask_dir = 'masks_png_convert'
mask_suffix = '.png'

# 获取所有图像和掩码文件名
img_filenames = os.listdir(osp.join(data_root, img_dir))
mask_filenames = os.listdir(osp.join(data_root, mask_dir))

# 确保图像和掩码数量一致
assert len(img_filenames) == len(mask_filenames), "Images and masks count do not match"

# 检查每个掩码文件
for mask_filename in mask_filenames:
    mask_path = osp.join(data_root, mask_dir, mask_filename)
    mask = Image.open(mask_path).convert('L')
    mask_array = np.array(mask)

    # 找出掩码中大于1的像素值
    if np.any(mask_array > 1):
        print(f"Found values > 1 in mask: {mask_filename}")

        # 打印掩码中大于1的像素值
        unique_labels = np.unique(mask_array)
        print(f"Unique labels in mask: {unique_labels}")

        # 加载对应的图像
        img_filename = mask_filename.replace(mask_suffix, '.jpg')
        img_path = osp.join(data_root, img_dir, img_filename)
        img = Image.open(img_path).convert('RGB')

        # 显示图像和掩码
        fig, axes = plt.subplots(1, 2, figsize=(12, 6))
        axes[0].imshow(img)
        axes[0].set_title('Image')
        axes[0].axis('off')
        axes[1].imshow(mask, cmap='gray')
        axes[1].set_title('Mask')
        axes[1].axis('off')