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https://github.com/john-okeefe/foliate-js.git
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john-okeefe
ffaceaf962
Implement a comprehensive panel detection system for manga and comics with automatic fallback chain for maximum compatibility. Core detector (detector.js): - PanelDetector class with in-memory caching - Lazy-loading of OpenCV and TensorFlow.js - Validation logic to filter poor detections - Cache management to avoid re-detection OpenCV edge detection (opencv.js): - Canny edge detection for panel boundaries - Contour finding with bounding box extraction - Size and aspect ratio filtering - Reading order sorting (top-to-bottom, left-to-right) ML-based detection (coco-ssd.js): - COCO-SSD pre-trained model integration - Object detection for irregular panel layouts - Rectangular filtering for panel-like regions - Handles edge cases where edge detection fails Grid-based fallback (grid.js): - Lightweight 3x3 grid detection - Empty cell detection via alpha channel analysis - Adjacent panel merging algorithm - Always works as final fallback The detection pipeline tries OpenCV first (fast, accurate), falls back to ML detection if validation fails, and uses grid detection as ultimate baseline.
48 lines
1.2 KiB
JavaScript
48 lines
1.2 KiB
JavaScript
// panel-detection/coco-ssd.js
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// ML-based panel detection using COCO-SSD
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export async function detectPanelsML(imageData, model) {
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const canvas = document.createElement("canvas");
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canvas.width = imageData.width;
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canvas.height = imageData.height;
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const ctx = canvas.getContext("2d");
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ctx.putImageData(imageData, 0, 0);
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const predictions = await model.detect(canvas);
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const panels = [];
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const imgWidth = imageData.width;
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const imgHeight = imageData.height;
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for (let i = 0; i < predictions.length; i++) {
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const pred = predictions[i];
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const [x, y, w, h] = pred.bbox;
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const aspectRatio = w / h;
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const isRectangular =
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aspectRatio > 0.3 &&
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aspectRatio < 5 &&
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w > imgWidth * 0.05 &&
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h > imgHeight * 0.05;
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if (isRectangular) {
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panels.push({
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id: `ml-${i}`,
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x: (x / imgWidth) * 100,
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y: (y / imgHeight) * 100,
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width: (w / imgWidth) * 100,
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height: (h / imgHeight) * 100,
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reading_order: i,
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});
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}
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}
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panels.sort((a, b) => {
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const rowA = Math.floor(a.y / 20);
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const rowB = Math.floor(b.y / 20);
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if (rowA !== rowB) return rowA - rowB;
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return a.x - b.x;
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});
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return panels.map((p, i) => ({ ...p, reading_order: i }));
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}
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