import { loadMLLibraries, getLibrariesStatus } from "./load-scripts.js"; // panel-detection/detector.js // Main panel detector with lazy-loaded fallback chain import { loadMLLibraries, getLibrariesStatus } from "./load-scripts.js"; export class PanelDetector { #cache = new Map(); #scriptsLoaded = false; async detectPanels(doc, index, force = false) { const cacheKey = `${doc.location?.pathname || ""}-${index}`; if (!force && this.#cache.has(cacheKey)) { return this.#cache.get(cacheKey); } const imageData = this.#extractImageData(doc); if (!imageData) { return { panels: [], method: "no-image", confidence: 0 }; } // Load ML libraries on first use if (!this.#scriptsLoaded) { const result = await loadMLLibraries(); if (!result.loaded) { console.warn( "ML libraries not available, using grid detection:", result.reason, ); // Fall back to grid immediately const { detectPanelsGrid } = await import("./grid.js"); const panels = detectPanelsGrid(imageData); this.#cache.set(cacheKey, { panels, method: "grid", confidence: 0.4, reason: result.reason, }); return { panels, method: "grid", confidence: 0.4, reason: result.reason, }; } this.#scriptsLoaded = true; } const result = await this.#runDetectionPipeline(imageData); this.#cache.set(cacheKey, result); return result; } #extractImageData(doc) { const img = doc.querySelector("img") || doc.querySelector("canvas"); if (!img) return null; const canvas = document.createElement("canvas"); canvas.width = img.naturalWidth || img.width; canvas.height = img.naturalHeight || img.height; const ctx = canvas.getContext("2d"); ctx.drawImage(img, 0, 0); return ctx.getImageData(0, 0, canvas.width, canvas.height); } async #runDetectionPipeline(imageData) { const { detectPanelsOpenCV } = await import("./opencv.js"); const { detectPanelsML } = await import("./coco-ssd.js"); const { detectPanelsGrid } = await import("./grid.js"); // Try OpenCV (uses global cv) try { const cv = globalThis.cv; if (cv && cv.Mat) { // Wait for OpenCV to be ready await new Promise((resolve, reject) => { const check = () => { if (cv && cv.Mat) resolve(); else if (cv && cv.readyState === "complete") reject(new Error("OpenCV failed to load")); else setTimeout(check, 50); }; check(); }); const panels = await detectPanelsOpenCV(imageData, cv); if (this.#validatePanels(panels, imageData)) { return { panels, method: "opencv", confidence: 0.85 }; } } } catch (e) { console.warn("OpenCV detection failed:", e); } // Try ML (uses global cocoSsd) try { const cocoSsd = globalThis.cocoSsd; if (cocoSsd) { // Wait for COCO-SSD to be ready if (!cocoSsd.load) { await new Promise((resolve) => setTimeout(resolve, 100)); } const panels = await detectPanelsML(imageData, cocoSsd); if (this.#validatePanels(panels, imageData)) { return { panels, method: "ml", confidence: 0.7 }; } } } catch (e) { console.warn("ML detection failed:", e); } // Grid fallback (always works) const panels = detectPanelsGrid(imageData); return { panels, method: "grid", confidence: 0.4 }; } #validatePanels(panels, imageData) { if (!panels || panels.length === 0) return false; if (panels.length > 30) return false; const imgArea = imageData.width * imageData.height; let totalPanelArea = 0; for (const panel of panels) { const panelArea = ((panel.width * panel.height) / 10000) * imgArea; totalPanelArea += panelArea; } const coverage = totalPanelArea / imgArea; return coverage > 0.1 && coverage < 0.95; } clear() { this.#cache.clear(); } // Expose library status for debugging getStatus() { return { ...getLibrariesStatus(), scriptsLoaded: this.#scriptsLoaded, cacheSize: this.#cache.size, }; } }