71 lines
2.7 KiB
Python
71 lines
2.7 KiB
Python
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# -*- coding:utf-8 -*-
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# @Author len
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# @Create 2023/12/25 14:55
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import cv2
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import numpy as np
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import random
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import os
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def process_image(bg_path, logo_path, output_path):
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background = cv2.imread(bg_path)
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logo = cv2.imread(logo_path, -1) # -1 表示尝试读取透明度通道
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if logo is None or background is None:
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print(f"无法读取图像，跳过 {bg_path} 和 {logo_path}")
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return
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# 检查标志图像是否有透明度通道
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if logo.shape[2] == 4:
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alpha_channel = logo[:, :, 3]
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else:
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alpha_channel = np.ones(logo.shape[:2], dtype=logo.dtype) * 255
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# 确保标志图像小于背景图像
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if logo.shape[1] > background.shape[1] or logo.shape[0] > background.shape[0]:
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scale_factor = min(background.shape[1] / logo.shape[1], background.shape[0] / logo.shape[0]) * 0.9
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else:
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scale_factor = random.uniform(0.5, 1.5)
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width = int(logo.shape[1] * scale_factor)
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height = int(logo.shape[0] * scale_factor)
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logo = cv2.resize(logo, (width, height))
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alpha_channel = cv2.resize(alpha_channel, (width, height))
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# 确保随机位置的计算是有效的
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x_offset = random.randint(0, max(0, background.shape[1] - width))
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y_offset = random.randint(0, max(0, background.shape[0] - height))
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# 合成图像
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for c in range(0, 3):
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background[y_offset:y_offset+height, x_offset:x_offset+width, c] = \
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logo[:, :, c] * (alpha_channel / 255.0) + \
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background[y_offset:y_offset+height, x_offset:x_offset+width, c] * (1.0 - alpha_channel / 255.0)
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# 保存结果到文件
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cv2.imwrite(output_path, background)
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# 文件夹路径
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backgrounds_path = r'D:\Waste\嵌入式\数据集\交通标志\1225交通标志\背景' # 替换为你的背景图片文件夹路径
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logos_path = r'D:\Waste\嵌入式\数据集\交通标志\1225交通标志\sign' # 替换为你的标志图片文件夹路径
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output_path = r'D:\Waste\嵌入式\数据集\交通标志\1225交通标志\生成' # 替换为你的输出文件夹路径
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# 确保输出路径存在
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if not os.path.exists(output_path):
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os.makedirs(output_path)
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backgrounds = [f for f in os.listdir(backgrounds_path) if f.endswith(('.png', '.jpg', '.jpeg'))]
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logos = [f for f in os.listdir(logos_path) if f.endswith(('.png', '.jpg', '.jpeg'))]
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# 为每个背景图片和每个标志图片组合
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for bg_file in backgrounds:
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for logo_file in logos:
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bg_full_path = os.path.join(backgrounds_path, bg_file)
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logo_full_path = os.path.join(logos_path, logo_file)
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output_full_path = os.path.join(output_path, f'combined_{bg_file[:-4]}_{logo_file}')
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process_image(bg_full_path, logo_full_path, output_full_path)
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print("批量处理完成！")
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