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从 Wikimedia Commons 抓取自由许可的真实图片素材(产品/物品/场景)。用于 U 盘素材准备、文档配图等需要真实照片但无 API key 的场景。
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
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| name | wikimedia-image-fetch |
| description | 从 Wikimedia Commons 抓取自由许可的真实图片素材(产品/物品/场景)。用于 U 盘素材准备、文档配图等需要真实照片但无 API key 的场景。 |
无需 API key,无需登录,所有图片 CC 自由许可可直接商用。 适用:考试素材、产品图配图、博客配图等需要"真实图片"而非占位的场景。
用:需要真实物体照片、品牌原型、场景图,且没有 API key。 不用:需要矢量图 / 矢量 logo(用 Wikimedia 后缀会搜到 SVG 但渲染要 librsvg);或需要 Unsplash 风格的高质量摄影(用 source.unsplash.com 需 key)。
import requests
PROXY = "http://127.0.0.1:7890" # WSL 下走 Clash 代理
HEADERS = {"User-Agent": "HermesBot/1.0 (your@email.com)"} # 真实 UA,默认 python-requests 会被拦
r = requests.get(
"https://commons.wikimedia.org/w/api.php",
params={
"action": "query",
"list": "search",
"srnamespace": 6, # File: 命名空间
"srsearch": "your keywords",
"srlimit": 15,
"format": "json",
},
headers=HEADERS,
proxies={"http": PROXY, "https": PROXY},
timeout=15,
)
hits = r.json()["query"]["search"] # [{"title": "File:XXX.jpg", ...}, ...]
r = requests.get(
"https://commons.wikimedia.org/w/api.php",
params={
"action": "query",
"titles": "File:XXX.jpg",
"prop": "imageinfo",
"iiprop": "url",
"iiurlwidth": 800, # 缩略图宽度,无则原图
"format": "json",
},
headers=HEADERS, proxies={"http": PROXY, "https": PROXY}, timeout=15,
)
url = r.json()["query"]["pages"][page_id]["imageinfo"][0]["thumburl"]
srsearch 跨所有 File 类型,PDF/.svg/.webm/.ogv 都会出来。必须过滤:
SKIP_EXT = (".pdf", ".svg", ".webm", ".ogv")
for h in hits:
title = h["title"]
if any(title.lower().endswith(ext) for ext in SKIP_EXT):
continue
return title # 第一张可用
否则会下到 PDF 封面而不是产品图(实测:bedside lamp 搜到 The Spirit lamp (serial) (IA spiritlampserial00doug).pdf)。
/api/rest_v1/page/summary/<title> 返回的 thumbnail.source 经常不准确(Apple Watch Ultra 2 搜到 Series 3 图)。直接用 search + imageinfo 两步法别图省事用 summary。
upload.wikimedia.org 限流。实测 sleep 60s 后恢复正常。代码里用 time.sleep(60) 重试一次即可。
见 scripts/fetch_wikimedia_images.py。
"Sony WH-1000XM4" 通常有图,但拼写要准"modern lamp" / "side-by-side refrigerator" 命中率高"product image"(太泛) / 纯品牌名(可能只搜到 logo SVG)from PIL import Image
img = Image.open(local_path)
pixels = list(img.getdata())
assert len(set(pixels[:5000])) > 10, "可能是纯色占位"
unique pixel 数 < 10 = 纯色块,> 100 = 真图。