新增16个AI技能：包含图像生成、视频剪辑、数据分析、智能查询等功能模块
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hmo
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.opencode/skills/image-service/scripts/merge_long_image.py
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251
.opencode/skills/image-service/scripts/merge_long_image.py
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#!/usr/bin/env python3
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"""
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长图拼接脚本 (Merge Long Image)
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将多张图片按顺序垂直拼接成一张微信长图
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Author: 翟星人
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"""
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import argparse
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import os
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import glob as glob_module
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from pathlib import Path
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from typing import List, Optional, Dict, Any
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from PIL import Image
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import numpy as np
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class LongImageMerger:
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"""长图拼接器"""
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def __init__(self, target_width: int = 1080):
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"""
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初始化拼接器
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Args:
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target_width: 目标宽度，默认1080（微信推荐宽度）
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"""
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self.target_width = target_width
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def _blend_images(self, img_top: Image.Image, img_bottom: Image.Image, blend_height: int) -> Image.Image:
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"""
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在两张图的接缝处创建渐变融合过渡
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Args:
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img_top: 上方图片
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img_bottom: 下方图片
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blend_height: 融合区域高度（像素）
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Returns:
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融合后的下方图片（顶部已与上方图片底部融合）
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"""
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blend_height = min(blend_height, img_top.height // 4, img_bottom.height // 4)
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top_region = img_top.crop((0, img_top.height - blend_height, img_top.width, img_top.height))
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bottom_region = img_bottom.crop((0, 0, img_bottom.width, blend_height))
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top_array = np.array(top_region, dtype=np.float32)
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bottom_array = np.array(bottom_region, dtype=np.float32)
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alpha = np.linspace(1, 0, blend_height).reshape(-1, 1, 1)
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blended_array = top_array * alpha + bottom_array * (1 - alpha)
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blended_array = np.clip(blended_array, 0, 255).astype(np.uint8)
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blended_region = Image.fromarray(blended_array)
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result = img_bottom.copy()
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result.paste(blended_region, (0, 0))
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return result
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def merge(
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self,
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image_paths: List[str],
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output_path: str,
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gap: int = 0,
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background_color: str = "white",
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blend: int = 0
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) -> Dict[str, Any]:
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"""
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拼接多张图片为长图
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Args:
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image_paths: 图片路径列表，按顺序拼接
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output_path: 输出文件路径
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gap: 图片之间的间隔像素，默认0
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background_color: 背景颜色，默认白色
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blend: 接缝融合过渡区域高度（像素），默认0不融合，推荐30-50
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Returns:
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包含拼接结果的字典
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"""
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if not image_paths:
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return {"success": False, "error": "没有提供图片路径"}
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valid_paths = []
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for p in image_paths:
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if os.path.exists(p):
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valid_paths.append(p)
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else:
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print(f"警告: 文件不存在，跳过 - {p}")
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if not valid_paths:
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return {"success": False, "error": "没有有效的图片文件"}
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try:
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imgs = [Image.open(p) for p in valid_paths]
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resized_imgs = []
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for img in imgs:
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if img.mode in ('RGBA', 'P'):
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img = img.convert('RGB')
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ratio = self.target_width / img.width
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new_height = int(img.height * ratio)
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resized = img.resize((self.target_width, new_height), Image.Resampling.LANCZOS)
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resized_imgs.append(resized)
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if blend > 0 and len(resized_imgs) > 1:
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for i in range(1, len(resized_imgs)):
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resized_imgs[i] = self._blend_images(resized_imgs[i-1], resized_imgs[i], blend)
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total_height = sum(img.height for img in resized_imgs) + gap * (len(resized_imgs) - 1)
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long_image = Image.new('RGB', (self.target_width, total_height), background_color)
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y_offset = 0
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for img in resized_imgs:
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long_image.paste(img, (0, y_offset))
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y_offset += img.height + gap
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Path(output_path).parent.mkdir(parents=True, exist_ok=True)
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long_image.save(output_path, quality=95)
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for img in imgs:
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img.close()
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for img in resized_imgs:
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img.close()
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return {
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"success": True,
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"saved_path": output_path,
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"width": self.target_width,
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"height": total_height,
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"image_count": len(resized_imgs)
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}
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except Exception as e:
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return {"success": False, "error": str(e)}
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def merge_from_pattern(
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self,
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pattern: str,
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output_path: str,
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sort_by: str = "name",
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gap: int = 0,
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background_color: str = "white",
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blend: int = 0
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) -> Dict[str, Any]:
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"""
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通过 glob 模式匹配图片并拼接
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Args:
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pattern: glob 模式，如 "*.png" 或 "generated_*.png"
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output_path: 输出文件路径
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sort_by: 排序方式 - "name"(文件名) / "time"(修改时间) / "none"(不排序)
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gap: 图片间隔
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background_color: 背景颜色
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blend: 接缝融合过渡高度
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Returns:
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包含拼接结果的字典
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"""
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image_paths = glob_module.glob(pattern)
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if not image_paths:
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return {"success": False, "error": f"没有找到匹配 '{pattern}' 的图片"}
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if sort_by == "name":
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image_paths.sort()
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elif sort_by == "time":
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image_paths.sort(key=lambda x: os.path.getmtime(x))
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print(f"找到 {len(image_paths)} 张图片:")
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for i, p in enumerate(image_paths, 1):
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print(f" {i}. {os.path.basename(p)}")
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return self.merge(image_paths, output_path, gap, background_color, blend)
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def main():
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"""命令行入口"""
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parser = argparse.ArgumentParser(
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description='长图拼接工具 - 将多张图片垂直拼接成微信长图',
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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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# 拼接指定图片
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python merge_long_image.py img1.png img2.png img3.png -o output.png
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# 使用通配符匹配
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python merge_long_image.py -p "generated_*.png" -o long_image.png
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# 指定宽度和间隔
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python merge_long_image.py -p "*.png" -o out.png -w 750 -g 20
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# 按修改时间排序
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python merge_long_image.py -p "*.png" -o out.png --sort time
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# 启用接缝融合过渡（推荐40px）
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python merge_long_image.py img1.png img2.png -o out.png --blend 40
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"""
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)
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parser.add_argument('images', nargs='*', help='要拼接的图片路径列表')
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parser.add_argument('-p', '--pattern', help='glob 模式匹配图片，如 "*.png"')
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parser.add_argument('-o', '--output', required=True, help='输出文件路径')
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parser.add_argument('-w', '--width', type=int, default=1080, help='目标宽度，默认1080')
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parser.add_argument('-g', '--gap', type=int, default=0, help='图片间隔像素，默认0')
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parser.add_argument('--sort', choices=['name', 'time', 'none'], default='name',
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help='排序方式：name(文件名)/time(修改时间)/none')
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parser.add_argument('--bg', default='white', help='背景颜色，默认 white')
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parser.add_argument('--blend', type=int, default=0,
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help='接缝融合过渡高度（像素），推荐30-50，默认0不融合')
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args = parser.parse_args()
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if not args.images and not args.pattern:
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parser.error("请提供图片路径列表或使用 -p 指定匹配模式")
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merger = LongImageMerger(target_width=args.width)
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if args.pattern:
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result = merger.merge_from_pattern(
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pattern=args.pattern,
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output_path=args.output,
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sort_by=args.sort,
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gap=args.gap,
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background_color=args.bg,
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blend=args.blend
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)
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else:
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result = merger.merge(
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image_paths=args.images,
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output_path=args.output,
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gap=args.gap,
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background_color=args.bg,
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blend=args.blend
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)
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if result["success"]:
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print(f"\n拼接成功！")
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print(f"输出文件: {result['saved_path']}")
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print(f"尺寸: {result['width']} x {result['height']}")
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print(f"共 {result['image_count']} 张图片")
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else:
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print(f"\n拼接失败: {result['error']}")
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if __name__ == "__main__":
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main()
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