feat(canvas): 图片转换插件 - 增加本地媒体转换节点与运行时

canvas-agent/python/lineart_runtime.py

@@ -0,0 +1,132 @@
+"""Small persistent worker for the local ControlNet Aux lineart detector.
+
+This worker only extracts a lineart control image. It does not load Stable
+Diffusion or a ControlNet generation pipeline, so it stays suitable for a
+CPU-only notebook. The Node Local Runtime owns the process and sends one JSON
+request per line; stdout is reserved for that protocol.
+"""
+
+from __future__ import annotations
+
+import base64
+import contextlib
+import io
+import json
+import os
+import re
+import sys
+from typing import Any
+
+from PIL import Image
+
+
+MODEL_ID = os.environ.get("CANVAS_LINEART_MODEL_ID", "lllyasviel/Annotators")
+MAX_INPUT_BYTES = 12 * 1024 * 1024
+DATA_URL_PATTERN = re.compile(r"^data:(image/(?:png|jpeg|webp));base64,([A-Za-z0-9+/=_-]+)$")
+DETECTOR: Any = None
+
+
+def emit(value: dict[str, Any]) -> None:
+    sys.stdout.write(json.dumps(value, ensure_ascii=False, separators=(",", ":")) + "\n")
+    sys.stdout.flush()
+
+
+def load_detector() -> Any:
+    global DETECTOR
+    if DETECTOR is not None:
+        return DETECTOR
+
+    try:
+        from controlnet_aux import LineartDetector
+
+        # The detector downloads only the lineart preprocessor weights from the
+        # configured Hugging Face cache. It is intentionally not a diffusion
+        # pipeline and never loads Stable Diffusion or ControlNet weights.
+        with contextlib.redirect_stdout(sys.stderr):
+            DETECTOR = LineartDetector.from_pretrained(MODEL_ID)
+    except Exception as error:  # pragma: no cover - depends on local files
+        raise RuntimeError("lineart_model_missing") from error
+    return DETECTOR
+
+
+def image_from_data_url(value: Any) -> Image.Image:
+    if not isinstance(value, str):
+        raise ValueError("lineart_input_invalid")
+    match = DATA_URL_PATTERN.fullmatch(value)
+    if not match:
+        raise ValueError("lineart_input_invalid")
+    try:
+        raw = base64.urlsafe_b64decode(match.group(2) + "=" * (-len(match.group(2)) % 4))
+    except Exception as error:
+        raise ValueError("lineart_input_invalid") from error
+    if not raw or len(raw) > MAX_INPUT_BYTES:
+        raise ValueError("lineart_input_invalid")
+    try:
+        image = Image.open(io.BytesIO(raw)).convert("RGB")
+        image.load()
+        return image
+    except Exception as error:
+        raise ValueError("lineart_input_invalid") from error
+
+
+def encode_png(image: Image.Image) -> str:
+    output = io.BytesIO()
+    image.save(output, format="PNG", optimize=True)
+    return base64.b64encode(output.getvalue()).decode("ascii")
+
+
+def handle(request: dict[str, Any]) -> dict[str, Any]:
+    image = image_from_data_url(request.get("dataUrl"))
+    try:
+        lineart = load_detector()(image)
+        if not isinstance(lineart, Image.Image):
+            raise RuntimeError("lineart_inference_failed")
+        return {
+            "ok": True,
+            "requestId": request.get("requestId"),
+            "mimeType": "image/png",
+            "width": lineart.width,
+            "height": lineart.height,
+            "modelId": MODEL_ID,
+            "device": "cpu",
+            "pngBase64": encode_png(lineart.convert("RGB")),
+        }
+    except RuntimeError:
+        raise
+    except Exception as error:  # pragma: no cover - depends on local runtime
+        raise RuntimeError("lineart_inference_failed") from error
+
+
+def main() -> None:
+    os.environ.setdefault("HF_HUB_DISABLE_TELEMETRY", "1")
+    os.environ.setdefault("HF_HUB_DISABLE_PROGRESS_BARS", "1")
+    os.environ.setdefault("HF_HUB_OFFLINE", "1")
+    os.environ.setdefault("TRANSFORMERS_OFFLINE", "1")
+
+    for line in sys.stdin:
+        # PowerShell and a few Windows launchers may prepend a UTF-8 BOM to
+        # the first piped line. The Node runtime sends plain UTF-8, but
+        # accepting the marker keeps the worker protocol tolerant for manual
+        # diagnostics as well.
+        line = line.lstrip("\ufeff").strip()
+        if not line:
+            continue
+        request_id: Any = None
+        try:
+            request = json.loads(line)
+            if not isinstance(request, dict):
+                raise ValueError("lineart_input_invalid")
+            request_id = request.get("requestId")
+            emit(handle(request))
+        except ValueError as error:
+            emit({"ok": False, "requestId": request_id, "code": str(error) or "lineart_input_invalid", "message": "线稿转换输入无效"})
+        except RuntimeError as error:
+            code = str(error) or "lineart_inference_failed"
+            message = "本地 AI 线稿模型或依赖尚未安装" if code == "lineart_model_missing" else "本地 AI 线稿推理失败"
+            emit({"ok": False, "requestId": request_id, "code": code, "message": message})
+        except Exception:
+            emit({"ok": False, "requestId": request_id, "code": "lineart_inference_failed", "message": "本地 AI 线稿推理失败"})
+
+
+if __name__ == "__main__":
+    main()