from PIL import Image
import numpy as np

# 读取原始图像
path = "output.bmp"
original_image = Image.open(path)
original_width, original_height = original_image.size


# 定义裁剪后的新高度
new_height = original_height - 400  # 上下各裁剪200像素

# 裁剪图像，上下各裁剪200像素
# 左上角坐标为(0, 200)，右下角坐标为(width, height-200)
cropped_image = original_image.crop(
    (0, 200, original_width, original_height-200))
cropped_image.show()

# 创建目标图像（1280x1024像素，灰度模式）
target_width, target_height = 1280, 1024
target_image = Image.new("L", (target_width, target_height), color=0)

# 计算图像放置位置
x_offset = (target_width - original_width) // 2
y_offset = (target_height - new_height) // 2

# 将原始图像放置在目标图像中央
target_image.paste(cropped_image, (x_offset, y_offset))

# 将目标图像转换为NumPy数组
target_array = np.array(target_image)

# # 在周围填充随机噪声
# noise_level = 256  # 随机噪声的灰度级别
# noise = np.random.randint(
#     0, noise_level, (target_height, target_width)).astype(np.uint8)
# target_array = np.where(target_array == 0, noise, target_array)

# # 创建包含噪声的新图像
# noisy_image = Image.fromarray(target_array.astype(np.uint8))

# # 保存为位图（BMP）图像
# noisy_image.save("black_"+path)

# 创建黑色填充
black_color = 0  # 黑色像素值为0
target_array[:y_offset, :] = black_color  # 上方填充
target_array[y_offset + original_height:, :] = black_color  # 下方填充
target_array[:, :x_offset] = black_color  # 左侧填充
target_array[:, x_offset + original_width:] = black_color  # 右侧填充

# 创建包含黑色填充的新图像
padded_image = Image.fromarray(target_array)

# 保存为位图（BMP）图像
padded_image.save("black_"+path)