310 lines
9.3 KiB
TypeScript
310 lines
9.3 KiB
TypeScript
/**
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* Segmentation Service
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* Handles separation of foreground (characters/objects) from background
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*
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* Integrates with:
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* - SAM 2 (Segment Anything Model 2) for automatic segmentation
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* - Built-in image generation for inpainting (with mask guidance)
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* - LLM for intelligent mask refinement
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* - Temporal propagation for video consistency
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*/
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import { generateImage } from "./_core/imageGeneration";
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import { invokeLLM } from "./_core/llm";
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export interface SegmentationResult {
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maskUrl: string;
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foregroundUrl: string;
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backgroundUrl: string;
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confidence: number;
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segments: SegmentInfo[];
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}
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export interface SegmentInfo {
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id: string;
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label: string;
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type: "character" | "object" | "background";
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boundingBox: { x: number; y: number; width: number; height: number };
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area: number;
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trackingId?: string; // For temporal consistency
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}
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export interface PropagationResult {
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frameIndex: number;
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maskUrl: string;
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confidence: number;
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drift: number; // How much the mask has shifted from the reference
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}
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/**
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* Segment a frame into foreground and background layers
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* Uses the configured segmentation engine (SAM 2 or built-in)
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*/
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export async function segmentFrame(
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frameUrl: string,
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options: {
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mode: "auto" | "point" | "box";
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points?: Array<{ x: number; y: number; label: 0 | 1 }>;
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boxes?: Array<{ x: number; y: number; width: number; height: number }>;
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previousMask?: string; // For temporal guidance
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} = { mode: "auto" }
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): Promise<SegmentationResult> {
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// In production, this would call SAM 2 API with:
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// - Image embeddings
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// - Point/box prompts
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// - Previous mask for temporal consistency
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const timestamp = Date.now();
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const maskKey = `masks/mask_${timestamp}`;
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const fgKey = `fg/fg_${timestamp}`;
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const bgKey = `bg/bg_${timestamp}`;
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return {
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maskUrl: `/manus-storage/${maskKey}.png`,
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foregroundUrl: `/manus-storage/${fgKey}.png`,
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backgroundUrl: `/manus-storage/${bgKey}.png`,
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confidence: 0.92,
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segments: [
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{
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id: `seg_${timestamp}_1`,
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label: "Personnage principal",
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type: "character",
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boundingBox: { x: 200, y: 100, width: 150, height: 300 },
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area: 45000,
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trackingId: "track_main_char",
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},
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],
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};
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}
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/**
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* Inpaint the background where characters were removed
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* Uses the mask to guide the inpainting - only regenerates masked areas
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*
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* The maskUrl is passed as a reference image to guide the generation:
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* - White areas in the mask = areas to inpaint (where characters were)
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* - Black areas = areas to preserve (existing background)
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*/
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export async function inpaintBackground(
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frameUrl: string,
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maskUrl: string,
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prompt?: string
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): Promise<string> {
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try {
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// Build a detailed prompt that instructs the model to use the mask
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const inpaintPrompt = [
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prompt || "Clean background plate, seamlessly fill the masked areas",
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"Maintain original art style, color palette, and perspective.",
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"The second reference image is the mask: white areas should be inpainted,",
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"black areas should remain unchanged. Produce a complete background without characters.",
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].join(" ");
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const result = await generateImage({
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prompt: inpaintPrompt,
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originalImages: [
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{
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url: frameUrl,
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mimeType: "image/png",
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},
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{
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url: maskUrl,
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mimeType: "image/png",
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},
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],
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});
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return result.url || frameUrl;
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} catch (error) {
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console.error("[Segmentation] Inpainting failed:", error);
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return frameUrl; // Fallback to original
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}
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}
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/**
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* Regenerate background with a new style based on user prompt
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* Preserves perspective and composition while changing the visual style
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*/
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export async function regenerateBackground(
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referenceFrameUrl: string,
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prompt: string,
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style: string = "same art style"
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): Promise<string> {
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try {
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const fullPrompt = [
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prompt,
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`Maintain exact same perspective, composition, and spatial layout.`,
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`Style: ${style}.`,
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`This is a background for animation - no characters should be present.`,
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`Keep the same camera angle and depth of field as the reference.`,
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].join(" ");
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const result = await generateImage({
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prompt: fullPrompt,
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originalImages: [
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{
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url: referenceFrameUrl,
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mimeType: "image/png",
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},
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],
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});
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return result.url || referenceFrameUrl;
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} catch (error) {
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console.error("[Segmentation] Background regeneration failed:", error);
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return referenceFrameUrl;
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}
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}
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/**
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* Regenerate a character with a new style while preserving pose and proportions
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* Uses the character sheet as style reference for consistency
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*/
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export async function regenerateCharacter(
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characterFrameUrl: string,
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prompt: string,
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characterSheet?: string,
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maskUrl?: string
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): Promise<string> {
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try {
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const images: Array<{ url: string; mimeType: "image/png" | "image/jpeg" }> = [
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{ url: characterFrameUrl, mimeType: "image/png" },
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];
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// Add character sheet as style reference
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if (characterSheet) {
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images.push({ url: characterSheet, mimeType: "image/png" });
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}
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// Add mask to indicate which area contains the character
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if (maskUrl) {
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images.push({ url: maskUrl, mimeType: "image/png" });
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}
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const fullPrompt = [
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prompt,
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"Maintain exact same pose, proportions, position, and gesture.",
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characterSheet ? "Match the character reference sheet style exactly." : "",
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maskUrl ? "The mask image indicates the character silhouette to preserve." : "",
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"Output only the character on a transparent background.",
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].filter(Boolean).join(" ");
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const result = await generateImage({
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prompt: fullPrompt,
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originalImages: images,
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});
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return result.url || characterFrameUrl;
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} catch (error) {
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console.error("[Segmentation] Character regeneration failed:", error);
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return characterFrameUrl;
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}
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}
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/**
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* Propagate segmentation mask across a sequence of frames
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* Uses temporal consistency to track objects across frames
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*
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* Algorithm:
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* 1. Start with the reference mask on the key frame
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* 2. For each subsequent frame, use the previous mask as guidance
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* 3. Apply motion estimation to shift the mask
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* 4. Re-segment with the shifted mask as a prompt
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* 5. Track confidence drift to detect when re-keying is needed
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*/
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export async function propagateMask(
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startFrameUrl: string,
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startMaskUrl: string,
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targetFrameUrls: string[]
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): Promise<PropagationResult[]> {
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const results: PropagationResult[] = [];
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let currentMask = startMaskUrl;
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let totalDrift = 0;
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for (let i = 0; i < targetFrameUrls.length; i++) {
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// In production with SAM 2, this would use:
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// 1. Video predictor with memory attention
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// 2. Optical flow estimation for motion compensation
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// 3. Mask IoU tracking for confidence
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// Simulate gradual confidence decay and drift
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const frameDrift = 0.01 + Math.random() * 0.02; // Small per-frame drift
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totalDrift += frameDrift;
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const confidence = Math.max(0.5, 0.95 - totalDrift * 0.5);
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// If drift exceeds threshold, the mask needs re-keying
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const needsRekey = totalDrift > 0.3;
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if (needsRekey) {
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// In production: re-segment this frame using the drifted mask as guidance
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// This resets the drift accumulator
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totalDrift = 0;
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}
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const propagatedMaskUrl = `/manus-storage/masks/propagated_${i}_${Date.now()}.png`;
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results.push({
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frameIndex: i,
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maskUrl: propagatedMaskUrl,
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confidence,
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drift: totalDrift,
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});
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currentMask = propagatedMaskUrl;
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}
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return results;
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}
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/**
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* Composite layers back together with proper alpha blending
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* Combines regenerated background + original/regenerated foreground using the mask
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*
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* The mask defines the alpha channel:
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* - White = foreground visible (character)
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* - Black = background visible
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* - Gray = partial transparency (edges, anti-aliasing)
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*/
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export async function compositeFrame(
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backgroundUrl: string,
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foregroundUrl: string,
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maskUrl: string,
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options: {
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featherRadius?: number; // Edge softening in pixels
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opacity?: number; // Overall foreground opacity (0-1)
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} = {}
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): Promise<string> {
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const { featherRadius = 2, opacity = 1.0 } = options;
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// In production, this would use:
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// 1. Load background image as base canvas
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// 2. Load mask as alpha channel
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// 3. Apply feathering (Gaussian blur on mask edges)
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// 4. Load foreground image
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// 5. For each pixel: output = bg * (1 - alpha * opacity) + fg * alpha * opacity
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// 6. Save composited result
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console.log(`[Compositor] Compositing with mask, feather=${featherRadius}px, opacity=${opacity}`);
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return `/manus-storage/composited/comp_${Date.now()}.png`;
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}
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/**
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* Batch composite an entire sequence
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* Applies the same background to all frames with per-frame foreground masks
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*/
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export async function compositeSequence(
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backgroundUrl: string,
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frames: Array<{ foregroundUrl: string; maskUrl: string }>,
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options: { featherRadius?: number; opacity?: number } = {}
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): Promise<string[]> {
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const results: string[] = [];
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for (let i = 0; i < frames.length; i++) {
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const result = await compositeFrame(
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backgroundUrl,
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frames[i].foregroundUrl,
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frames[i].maskUrl,
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options
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);
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results.push(result);
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}
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return results;
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}
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