feat(canvas): 画布节点 - 恢复批量创作表与转换能力

web/src/lib/media-conversion/contracts.ts

@@ -0,0 +1,89 @@
+import type { CanvasNodeData } from "@/types/canvas";
+
+export const MEDIA_CONVERSION_SCHEMA_VERSION = 1 as const;
+
+export const MEDIA_CONVERSION_NODE_TYPE = "media-conversion" as const;
+
+export type MediaConversionOperation = "grayscale" | "edge-canny" | "lineart" | "depth" | "pose" | "cutout";
+export type MediaConversionStatus = "idle" | "processing" | "completed" | "stale" | "skipped" | "unavailable" | "error";
+export type MediaConversionOutputKind = "image" | "video";
+
+export type MediaConversionNodeState = {
+    schemaVersion: typeof MEDIA_CONVERSION_SCHEMA_VERSION;
+    operation: MediaConversionOperation;
+    status: MediaConversionStatus;
+    sourceNodeId?: string;
+    sourceFingerprint?: string;
+    outputKind?: MediaConversionOutputKind;
+    resultStorageKey?: string;
+    resultWidth?: number;
+    resultHeight?: number;
+    detectedPeople?: number;
+    errorCode?: string;
+    errorMessage?: string;
+    startedAt?: string;
+    updatedAt?: string;
+};
+
+export const MEDIA_CONVERSION_OPERATION_LABELS: Record<MediaConversionOperation, string> = {
+    grayscale: "灰度图",
+    "edge-canny": "Canny 边缘",
+    lineart: "AI 线稿",
+    depth: "深度图",
+    pose: "姿态骨架",
+    cutout: "透明抠图",
+};
+
+export const MEDIA_CONVERSION_OPERATION_DESCRIPTIONS: Record<MediaConversionOperation, string> = {
+    grayscale: "普通图像算法，适合先检查明暗层次",
+    "edge-canny": "普通图像算法，提取清晰轮廓",
+    lineart: "本地 ControlNet Aux 线稿预处理，首次运行需要加载模型",
+    depth: "本地 Depth Anything V2 Small，首次运行需要加载模型",
+    pose: "本地 OpenPose 人体骨架预处理，未检测到人物时会跳过",
+    cutout: "需要安装并验证本地抠图模型",
+};
+
+export function createDefaultMediaConversionState(): MediaConversionNodeState {
+    return {
+        schemaVersion: MEDIA_CONVERSION_SCHEMA_VERSION,
+        operation: "edge-canny",
+        status: "idle",
+    };
+}
+
+export function mediaConversionSourceFingerprint(node: CanvasNodeData) {
+    const metadata = node.metadata;
+    const source = [
+        node.id,
+        metadata?.storageKey || "",
+        compactSource(metadata?.content || metadata?.previewContent || ""),
+        metadata?.mimeType || "",
+        metadata?.bytes || "",
+        metadata?.naturalWidth || "",
+        metadata?.naturalHeight || "",
+        metadata?.durationMs || "",
+    ].join("|");
+    let hash = 2166136261;
+    for (let index = 0; index < source.length; index += 1) {
+        hash ^= source.charCodeAt(index);
+        hash = Math.imul(hash, 16777619);
+    }
+    return `v1-${(hash >>> 0).toString(16).padStart(8, "0")}`;
+}
+
+export function mediaConversionOperationLabel(operation: MediaConversionOperation) {
+    return MEDIA_CONVERSION_OPERATION_LABELS[operation];
+}
+
+export function mediaConversionOperationDescription(operation: MediaConversionOperation) {
+    return MEDIA_CONVERSION_OPERATION_DESCRIPTIONS[operation];
+}
+
+export function isLocalImageOperation(operation: MediaConversionOperation) {
+    return operation === "grayscale" || operation === "edge-canny";
+}
+
+function compactSource(value: string) {
+    if (value.length <= 2048) return value;
+    return `${value.slice(0, 1024)}|${value.slice(-1024)}|${value.length}`;
+}