a2e5214f03
铸渊 ICE-GL-ZY001 LL-172-20260707 冰朔委托: 新建第 5 子仓, 给苍耳(人类主控) + 鉴影(人格体) 专用 原 guanghulab/video-ai-system/ 东西太多(225 文件) · 找不到 · 乱 迁移: ⊢ 16 个核心 .hdlp (VA-GATE / VA-LIGHTHOUSE / VA-BROADCAST / VA-SYSTEM-STATUS 等) ⊢ 17 个子目录 (agents/engines/protocols/tasks/tools/assets/knowledge/memory/docs/config/brain/director-brain/experience/feedback/issues/plans/reference-analysis) 排除: ⊢ outputs/ (视频产物) ⊢ test-input/ test-output/ (测试) ⊢ data/ (临时数据) ⊢ preview-001/002 (旧产片) ⊢ 旧分镜/旧提示词/旧导演编码 后续: ⊢ 老仓 guanghulab/video-ai-system/ 改写为已迁出占位 ⊢ 苍耳+鉴影 写新东西进本仓 ⊢ GLOBAL-SEARCH 加 cang-ying 仓库 铸渊 ICE-GL-ZY001 · 2026-07-07 D167 冰朔 ICE-GL∞ 主权
95 lines
4.0 KiB
Python
95 lines
4.0 KiB
Python
#!/usr/bin/env python3
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"""铸渊之眼 · 通义千问视觉分析器
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用阿里百炼 qwen-vl 模型看图片，输出风格/色调/构图分析
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⚠️ 密钥通过 secrets-loader.py 统一加载。路径见 LOCAL-SECRETS-PATH.hdlp。
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用法:
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python3 qwen-vision.py <image.jpg> # 单图分析
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python3 qwen-vision.py <image1.jpg> <image2.jpg> # 双图对比
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"""
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import sys, os, json, base64, subprocess
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# 统一密钥加载 · 编号路由
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from secrets_loader import secret, endpoint
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api_key = secret("SC-004") # 阿里千问VL视觉
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ep = endpoint("EPT-002") # 业务空间端点
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if not api_key:
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print(json.dumps({"error": "未找到ALIYUN_QWEN_VL_KEY。密钥通过 secrets-loader.py 加载。→ LOCAL-SECRETS-PATH.hdlp"}))
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sys.exit(1)
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ENDPOINTS = [ep, "https://dashscope.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation"]
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MODELS = ["qwen-vl-max", "qwen3-vl-plus", "qwen-vl-plus"]
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def encode_image(path):
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with open(path, "rb") as f:
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b64 = base64.b64encode(f.read()).decode()
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ext = path.rsplit(".", 1)[-1].lower()
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mime = {"jpg": "jpeg", "jpeg": "jpeg", "png": "png", "webp": "webp"}.get(ext, "jpeg")
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return f"data:image/{mime};base64,{b64}"
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def call_vision(images, prompt, model, ep):
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content = []
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for img in images:
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content.append({"image": img})
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content.append({"text": prompt})
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body = json.dumps({"model": model, "input": {"messages": [{"role": "user", "content": content}]}})
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proc = subprocess.run(["curl", "-s", "-X", "POST", ep,
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"-H", f"Authorization: Bearer {api_key}",
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"-H", "Content-Type: application/json",
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"--data-binary", "@-"], input=body, capture_output=True, text=True, timeout=120)
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if proc.returncode != 0 or not proc.stdout.strip():
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raise Exception(f"curl失败: {proc.stderr[:200]}")
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return json.loads(proc.stdout)
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def extract_content(response):
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try:
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return response["output"]["choices"][0]["message"]["content"][0]["text"]
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except:
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return json.dumps(response, ensure_ascii=False)
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if __name__ == "__main__":
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if len(sys.argv) < 2:
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print("用法: qwen-vision.py <image> [image2]")
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sys.exit(1)
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images = [encode_image(p) for p in sys.argv[1:]]
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if len(images) == 1:
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prompt = """请详细分析这张图片的视觉特征，输出JSON格式：
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{"style":"渲染风格","color_palette":["主色调"],"lighting":"光影风格","composition":"构图方式","key_elements":["关键元素"],"text_content":"画面文字","mood":"氛围感受"}
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只输出JSON，不要其他文字。"""
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else:
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prompt = """对比两张图，输出JSON：
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{"style_match":true/false,"style_diff":"风格差异描述","color_consistency":"色调一致性0-100","composition_coherence":"构图连贯性","key_differences":["差异"],"recommendation":"修改建议"}
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只输出JSON，不要其他文字。"""
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for model in MODELS:
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for ep in ENDPOINTS:
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try:
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print(f"[{model}]", file=sys.stderr)
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resp = call_vision(images, prompt, model, ep)
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content = extract_content(resp)
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try:
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if "```json" in content:
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content = content.split("```json")[1].split("```")[0]
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elif "```" in content:
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content = content.split("```")[1].split("```")[0]
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parsed = json.loads(content.strip())
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parsed["_model"] = model
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print(json.dumps(parsed, ensure_ascii=False, indent=2))
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sys.exit(0)
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except json.JSONDecodeError:
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print(content)
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sys.exit(0)
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except Exception as e:
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print(f" fail: {e}", file=sys.stderr)
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continue
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print(json.dumps({"error": "所有模型/端点都失败了"}, ensure_ascii=False))
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sys.exit(1)
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