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douboer
258
remove_background.py
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258
remove_background.py
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"""
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图片去背景工具
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使用rembg库自动去除图片背景
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"""
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import os
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import argparse
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from pathlib import Path
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from rembg import remove, new_session
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from PIL import Image
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# 支持HEIC格式
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try:
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from pillow_heif import register_heif_opener
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register_heif_opener()
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HEIC_SUPPORTED = True
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except ImportError:
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HEIC_SUPPORTED = False
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def str2bool(v):
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"""将字符串转换为布尔值"""
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if isinstance(v, bool):
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return v
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if v.lower() in ('yes', 'true', 't', 'y', '1'):
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return True
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elif v.lower() in ('no', 'false', 'f', 'n', '0'):
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return False
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else:
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raise argparse.ArgumentTypeError('布尔值应为true或false')
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def remove_background(input_path, output_path, session=None, **kwargs):
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"""
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去除图片背景
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Args:
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input_path: 输入图片路径
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output_path: 输出图片路径
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session: rembg会话对象（可选）
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**kwargs: 其他参数，如alpha_matting相关参数
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"""
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print(f"正在处理: {input_path}")
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# 读取输入图片
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input_image = Image.open(input_path)
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# 去除背景
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output_image = remove(input_image, session=session, **kwargs)
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# 保存输出图片
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output_image.save(output_path)
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print(f"已保存: {output_path}")
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def process_images_folder(input_folder, output_folder, model_name="u2net",
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alpha_matting=False, alpha_matting_foreground_threshold=240,
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alpha_matting_background_threshold=10, alpha_matting_erode_size=10,
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post_process_mask=False):
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"""
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批量处理文件夹中的所有图片
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Args:
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input_folder: 输入文件夹路径
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output_folder: 输出文件夹路径
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model_name: 模型名称，可选值:
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- u2net (默认): 通用模型
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- u2netp: 轻量版u2net
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- u2net_human_seg: 人物分割
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- silueta: 精简版u2net (43MB)
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- isnet-general-use: 新的通用模型
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- isnet-anime: 动漫角色高精度分割
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- birefnet-general: 通用模型
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- birefnet-portrait: 人像模型
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alpha_matting: 是否启用alpha matting后处理（改善边缘质量）
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alpha_matting_foreground_threshold: 前景阈值 (0-255)，值越大保留越多前景
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alpha_matting_background_threshold: 背景阈值 (0-255)，值越大去除越多背景
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alpha_matting_erode_size: 侵蚀大小，用于平滑边缘
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post_process_mask: 是否启用mask后处理
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"""
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# 创建输出文件夹
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Path(output_folder).mkdir(parents=True, exist_ok=True)
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# 创建会话（重用会话可以提高性能）
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print(f"使用模型: {model_name}")
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session = new_session(model_name)
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# 支持的图片格式
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image_extensions = {'.jpg', '.jpeg', '.png', '.bmp', '.webp'}
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if HEIC_SUPPORTED:
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image_extensions.update({'.heic', '.heif'})
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else:
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print("提示: 未安装pillow-heif，HEIC格式不可用。安装方法: pip install pillow-heif")
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# 获取所有图片文件
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input_path = Path(input_folder)
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image_files = [f for f in input_path.iterdir()
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if f.is_file() and f.suffix.lower() in image_extensions]
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if not image_files:
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print(f"在 {input_folder} 中没有找到图片文件")
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return
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print(f"找到 {len(image_files)} 张图片，开始处理...")
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print(f"Alpha Matting: {'启用' if alpha_matting else '禁用'}")
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if alpha_matting:
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print(f" - 前景阈值: {alpha_matting_foreground_threshold}")
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print(f" - 背景阈值: {alpha_matting_background_threshold}")
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print(f" - 侵蚀大小: {alpha_matting_erode_size}")
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print(f"Mask后处理: {'启用' if post_process_mask else '禁用'}")
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print("-" * 50)
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# 处理每张图片
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for i, image_file in enumerate(image_files, 1):
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try:
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# 输出文件名（保持原始名称，改为PNG格式以支持透明背景）
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output_filename = image_file.stem + '_nobg.png'
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output_path = Path(output_folder) / output_filename
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print(f"[{i}/{len(image_files)}] ", end="")
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remove_background(
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str(image_file),
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str(output_path),
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session=session,
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alpha_matting=alpha_matting,
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alpha_matting_foreground_threshold=alpha_matting_foreground_threshold,
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alpha_matting_background_threshold=alpha_matting_background_threshold,
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alpha_matting_erode_size=alpha_matting_erode_size,
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post_process_mask=post_process_mask
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)
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except Exception as e:
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print(f"处理 {image_file.name} 时出错: {e}")
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print("-" * 50)
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print(f"处理完成！结果保存在 {output_folder} 文件夹中")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(
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description='图片去背景工具 - 使用rembg自动去除图片背景',
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog='''
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示例用法:
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# 使用默认参数处理images文件夹
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python remove_background.py
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# 处理单个文件
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python remove_background.py input.jpg output.png
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# 处理指定文件夹
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python remove_background.py my_images/ my_output/
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# 使用不同模型
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python remove_background.py input.jpg output.png -m birefnet-portrait
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# 自定义alpha matting参数
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python remove_background.py input.jpg output.png -ft 260 -bt 12 -es 5
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'''
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)
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# 必需参数
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parser.add_argument('input', nargs='?', default='images',
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help='输入文件或文件夹路径（默认: images）')
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parser.add_argument('output', nargs='?', default=None,
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help='输出文件或文件夹路径（可选，默认为output/）')
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# 模型选择
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parser.add_argument('-m', '--model', default='isnet-general-use',
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choices=['u2net', 'u2netp', 'u2net_human_seg', 'silueta',
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'isnet-general-use', 'isnet-anime',
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'birefnet-general', 'birefnet-general-lite',
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'birefnet-portrait', 'birefnet-dis',
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'birefnet-hrsod', 'birefnet-cod', 'birefnet-massive'],
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help='选择使用的模型 (默认: isnet-general-use)')
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# Alpha Matting参数
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parser.add_argument('-a', '--alpha-matting', type=str2bool, nargs='?', const=True, default=True,
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metavar='true/false',
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help='启用alpha matting后处理（默认: true）。用法: -a 或 -a true 或 -a false')
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parser.add_argument('-ft', '--foreground-threshold', type=int, default=245,
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help='前景阈值 (0-255)，值越大保留越多细节 (默认: 245)')
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parser.add_argument('-bt', '--background-threshold', type=int, default=8,
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help='背景阈值 (0-255)，值越大去除越多背景 (默认: 8)')
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parser.add_argument('-es', '--erode-size', type=int, default=2,
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help='侵蚀大小，用于平滑边缘，值越大越平滑但可能丢失细节 (默认: 2)')
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# 其他选项
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parser.add_argument('-p', '--post-process', type=str2bool, nargs='?', const=True, default=True,
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metavar='true/false',
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help='启用mask后处理（默认: true）。用法: -p 或 -p true 或 -p false')
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args = parser.parse_args()
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print("=" * 50)
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print("图片去背景工具")
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print("=" * 50)
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# 判断输入是文件还是文件夹
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input_path = Path(args.input)
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if not input_path.exists():
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print(f"错误: 输入路径不存在: {args.input}")
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exit(1)
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# 处理单个文件
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if input_path.is_file():
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# 确定输出路径
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if args.output is None:
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output_path = input_path.parent / 'output' / (input_path.stem + '_nobg.png')
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output_path.parent.mkdir(parents=True, exist_ok=True)
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else:
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output_path = Path(args.output)
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output_path.parent.mkdir(parents=True, exist_ok=True)
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print(f"输入文件: {input_path}")
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print(f"输出文件: {output_path}")
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print(f"模型: {args.model}")
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print(f"Alpha Matting: {'启用' if args.alpha_matting else '禁用'}")
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if args.alpha_matting:
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print(f" - 前景阈值: {args.foreground_threshold}")
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print(f" - 背景阈值: {args.background_threshold}")
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print(f" - 侵蚀大小: {args.erode_size}")
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print(f"Mask后处理: {'启用' if args.post_process else '禁用'}")
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print("-" * 50)
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# 创建会话
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session = new_session(args.model)
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# 处理图片
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remove_background(
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str(input_path),
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str(output_path),
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session=session,
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alpha_matting=args.alpha_matting,
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alpha_matting_foreground_threshold=args.foreground_threshold,
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alpha_matting_background_threshold=args.background_threshold,
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alpha_matting_erode_size=args.erode_size,
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post_process_mask=args.post_process
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)
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print("-" * 50)
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print(f"处理完成！结果保存在: {output_path}")
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# 处理文件夹
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elif input_path.is_dir():
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output_folder = args.output if args.output else 'output'
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process_images_folder(
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str(input_path),
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output_folder,
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model_name=args.model,
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alpha_matting=args.alpha_matting,
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alpha_matting_foreground_threshold=args.foreground_threshold,
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alpha_matting_background_threshold=args.background_threshold,
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alpha_matting_erode_size=args.erode_size,
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post_process_mask=args.post_process
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)
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else:
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print(f"错误: 不支持的输入类型: {args.input}")
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exit(1)
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