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import os
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import time
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from PIL import Image
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# 导入配置
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from Config import target_width, image_quality, compressed_images_dir
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def process_image(img_path, target_width=target_width):
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"""
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处理图像
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:param img_path: 输入图像路径
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:param target_width: 目标宽度（默认587像素，根据用户提供的好用图片尺寸）
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:param output_path: 输出结果的文件路径（可选）
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:param raw_output_path: 原始OCR结果的输出文件路径（可选）
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:return: OCR识别结果
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"""
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start_time = time.time()
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# 图片预处理 - 缩小图片尺寸到指定宽度
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img = Image.open(img_path)
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width, height = img.size
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print(f"原始图片尺寸: {width}x{height}")
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# 计算缩放比例，保持纵横比
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scale = target_width / width
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new_width = target_width
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new_height = int(height * scale)
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print(f"目标图片尺寸: {new_width}x{new_height}")
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# 缩放图像
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resized_img = img.resize((new_width, new_height), Image.LANCZOS)
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# 确保压缩图片目录存在
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os.makedirs(compressed_images_dir, exist_ok=True)
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# 获取原始文件名并创建新的输出路径
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file_name = os.path.basename(img_path)
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output_name = os.path.splitext(file_name)[0] + "_compressed.jpg"
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output_path = os.path.join(compressed_images_dir, output_name)
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# 保存缩小后的图片
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resized_img.convert('RGB').save(output_path, 'JPEG', quality=image_quality, optimize=True)
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print(f"图片已缩小: {width}x{height} -> {new_width}x{new_height}")
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# 释放内存
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del resized_img
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img.close()
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del img
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if __name__ == "__main__":
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import glob
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from Config import images_dir
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# 处理Images目录下的所有PNG图片
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image_files = glob.glob(os.path.join(images_dir, "page_*.png"))
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print(f"找到{len(image_files)}个图片文件需要处理")
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for i, img_path in enumerate(image_files):
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print(f"[{i+1}/{len(image_files)}] 处理图片: {os.path.basename(img_path)}")
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process_image(img_path)
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print(f"所有图片处理完成，压缩后的图片保存在: {compressed_images_dir}") |
