120 lines
4.7 KiB
Python
120 lines
4.7 KiB
Python
# -*- coding: utf-8 -*-
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"""
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从 PPT 提取的原始素材生成网站用图：
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1. logo 与 7 张黑底产品图：边缘 flood-fill 镂空（背景变透明，适配深色网页）
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2. 水培架图背景复杂（39% 均匀度），不镂空，走统一描边容器展示
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3. 截图/场景/照片转 WebP 压缩；二维码保持 PNG 无损
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用法: uv run --with pillow python3 tools/process_images.py <pptx解压目录>/ppt/media <输出目录>
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"""
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import sys
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from collections import deque
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from pathlib import Path
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from PIL import Image
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src = Path(sys.argv[1])
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out = Path(sys.argv[2])
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out.mkdir(parents=True, exist_ok=True)
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RENAME = {
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'image2.png': 'logo.png', # 原样无损输出（见 PASS_THROUGH）
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'image1.jpeg': 'hero-bg.webp', # v2 起不再做 hero 背景，仅作 og:image
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'image3.png': 'about-main.webp', # v2 起弃用（PPT 拼贴图有白缝）
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'image4.png': 'about-base.webp',
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'image5.png': 'collar-sg03-mini.webp',
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'image13.png': 'collar-sg03.webp',
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'image10.png': 'ear-tag-st01.webp',
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'image11.png': 'base-station-bg01.webp',
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'image12.png': 'grazing-scene-1.webp',
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'image18.png': 'grazing-scene-2.webp',
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'image19.png': 'hydroponics-hs01.webp',
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'image20.png': 'planting-scene.webp',
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'image31.png': 'terminal-bb03.webp',
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'image32.png': 'uwb-tag-sl01.webp',
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'image33.png': 'bt-tag-st02.webp',
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'image29.png': 'asset-scene-1.webp',
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'image30.jpeg': 'asset-scene-2.webp',
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'image34.png': 'platform-grazing-1.webp',
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'image35.png': 'platform-grazing-app.webp',
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'image36.png': 'platform-planting-1.webp',
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'image37.png': 'platform-planting-2.webp',
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'image38.png': 'platform-asset-1.webp',
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'image39.png': 'platform-asset-2.webp',
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'image40.png': 'custom-liangchang-1.webp',
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'image41.png': 'custom-liangchang-2.webp',
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'image42.png': 'custom-simulation.webp',
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'image43.png': 'custom-agent.webp',
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'image44.png': 'qrcode.png',
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}
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# 这些图做边缘 flood-fill 镂空（检测过：边缘色 96-100% 均匀的纯黑底）
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# 注意：logo 不镂空——其底色 #000020 与四角检测色差超容差，v2 曾清成斑驳残留导致看不清
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CUTOUT = {
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'image5.png', 'image13.png', 'image10.png', 'image11.png',
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'image31.png', 'image32.png', 'image33.png',
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}
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CUTOUT_TOL = 30 # 曼哈顿距离阈值，宁小勿大：黑底纯度高，产品暗部 (#20 系) 距离约 96 不会被误清
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def cutout_bg(path: Path, tol: int) -> Image.Image:
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"""从画布四边缘 flood-fill 清除均匀底色，只清与边缘连通的背景，不动被包围的内容"""
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im = Image.open(path).convert('RGBA')
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w, h = im.size
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px = im.load()
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corners = [px[0, 0], px[w-1, 0], px[0, h-1], px[w-1, h-1]]
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bg = tuple(sum(c[i] for c in corners) // 4 for i in range(3))
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def is_bg(p):
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if p[3] < 10:
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return True # 原本就是透明的像素直接视为背景
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return abs(p[0]-bg[0]) + abs(p[1]-bg[1]) + abs(p[2]-bg[2]) <= tol
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seen = [[False]*w for _ in range(h)]
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q = deque()
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for x in range(w):
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q.extend(((x, 0), (x, h-1)))
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for y in range(h):
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q.extend(((0, y), (w-1, y)))
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cleared = 0
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while q:
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x, y = q.popleft()
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if x < 0 or x >= w or y < 0 or y >= h or seen[y][x]:
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continue
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seen[y][x] = True
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p = px[x, y]
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if not is_bg(p):
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continue
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px[x, y] = (0, 0, 0, 0)
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cleared += 1
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q.extend(((x+1, y), (x-1, y), (x, y+1), (x, y-1)))
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ratio = cleared / (w * h)
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# 镂空比例健全性检查：太低=没清干净，太高=误伤内容
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if not 0.10 < ratio < 0.92:
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raise SystemExit(f'镂空异常 {path.name}: 清除 {ratio:.0%}，需人工检查')
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return im
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# 原样无损拷贝：logo 色块文字经不起有损压缩，二维码必须无损
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PASS_THROUGH = {'image2.png', 'image44.png'}
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for src_name, dst_name in RENAME.items():
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src_path = src / src_name
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if not src_path.exists():
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print(f' 跳过缺失: {src_name}')
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continue
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dst_path = out / dst_name
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if src_name in PASS_THROUGH:
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Image.open(src_path).save(dst_path)
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elif src_name in CUTOUT:
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im = cutout_bg(src_path, CUTOUT_TOL)
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# 镂空图必须带 alpha，webp 无损存 alpha（有损会弄脏半透明边缘）
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im.save(dst_path, 'WEBP', quality=100, lossless=True, method=6)
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else:
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im = Image.open(src_path).convert('RGB')
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if im.width > 1600:
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im = im.resize((1600, round(im.height * 1600 / im.width)), Image.LANCZOS)
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im.save(dst_path, 'WEBP', quality=82, method=6)
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kb = dst_path.stat().st_size // 1024
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tag = ' [镂空]' if src_name in CUTOUT else ''
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print(f' {src_name:14s} -> {dst_name:28s} {kb}KB{tag}')
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print(f'完成，共 {len(RENAME)} 张 -> {out}')
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