bc7d5a3cc7
Adds a 3-phase pipeline to populate a HexMap from a source image using Claude's vision capabilities instead of naive pixel-color matching: Phase 1 (extract-submaps): crops annotated submap PNGs per hex, including center + 6 neighbours with SVG overlay. Phase 2: Claude classifies submaps in a Code session, writing classifications.json — resumable across sessions. Phase 3 (import-from-json): reads classifications.json into the DB. Also adds assemble-map.ts to reconstruct a full image from a Leaflet tile pyramid (used to recover the Aventurien source map from kiepenkerl). Adds CLAUDE.md documenting the approach, scale constants (PIXELS_PER_MEILE=8, hexSize=40 = 10 Meilen/Hex), and the Nord/Mitte/Süd region split for the Aventurien map. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
113 lines
3.4 KiB
TypeScript
113 lines
3.4 KiB
TypeScript
/**
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* Reconstruct a full map image from a Leaflet tile pyramid (zoom level z).
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*
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* Usage:
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* npx tsx pipeline/assemble-map.ts <tiles-dir> <output-image> [zoom-level]
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*
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* The tiles-dir must contain subdirectories named by x-index, each containing
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* y-index.jpg files (standard Leaflet tile layout: {z}/{x}/{y}.jpg).
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*
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* Example:
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* npx tsx pipeline/assemble-map.ts pipeline/source/aventurien-tiles-z6 pipeline/source/aventurien.jpg
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*/
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import sharp from 'sharp';
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import { readdirSync, existsSync } from 'fs';
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import { join, resolve } from 'path';
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const TILE_SIZE = 256;
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async function assembleTiles(tilesDir: string, outputPath: string) {
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if (!existsSync(tilesDir)) {
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console.error(`Tiles directory not found: ${tilesDir}`);
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process.exit(1);
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}
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// Discover grid dimensions from directory structure
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const xDirs = readdirSync(tilesDir)
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.map(Number)
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.filter(n => !isNaN(n))
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.sort((a, b) => a - b);
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if (xDirs.length === 0) {
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console.error('No tile columns found in', tilesDir);
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process.exit(1);
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}
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const maxX = Math.max(...xDirs);
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// Count rows from first column
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const firstColDir = join(tilesDir, String(xDirs[0]));
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const yFiles = readdirSync(firstColDir)
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.map(f => parseInt(f))
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.filter(n => !isNaN(n))
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.sort((a, b) => a - b);
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const maxY = Math.max(...yFiles);
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const tilesX = maxX + 1;
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const tilesY = maxY + 1;
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const totalWidth = tilesX * TILE_SIZE;
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const totalHeight = tilesY * TILE_SIZE;
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console.log(`Grid: ${tilesX}×${tilesY} tiles → canvas ${totalWidth}×${totalHeight}px`);
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const composites: sharp.OverlayOptions[] = [];
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let loaded = 0;
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for (const x of xDirs) {
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const colDir = join(tilesDir, String(x));
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const yFiles = readdirSync(colDir)
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.map(f => parseInt(f))
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.filter(n => !isNaN(n))
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.sort((a, b) => a - b);
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for (const y of yFiles) {
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const tilePath = join(colDir, `${y}.jpg`);
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if (!existsSync(tilePath)) continue;
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composites.push({
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input: tilePath,
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left: x * TILE_SIZE,
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top: y * TILE_SIZE,
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});
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loaded++;
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}
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}
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console.log(`Compositing ${loaded} tiles...`);
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// Process in batches to avoid hitting sharp's composite limit
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const BATCH = 200;
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let canvas = sharp({
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create: { width: totalWidth, height: totalHeight, channels: 3, background: { r: 42, g: 85, b: 116 } },
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}).jpeg({ quality: 92 });
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// sharp supports all composites in one call for reasonable counts
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await sharp({
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create: { width: totalWidth, height: totalHeight, channels: 3, background: { r: 42, g: 85, b: 116 } },
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})
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.composite(composites)
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.jpeg({ quality: 92 })
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.toFile(outputPath);
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console.log(`Assembled → ${outputPath}`);
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// Print map config hint
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const actualW = tilesX * TILE_SIZE;
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const actualH = tilesY * TILE_SIZE;
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console.log(`\nMap config hint:`);
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console.log(` imageSize: [${actualW}, ${actualH}]`);
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console.log(` PIXELS_PER_MEILE: 8`);
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console.log(` 10 Meilen/Hex → hexSize: 40 (~${Math.round(actualW/80)}×${Math.round(actualH/69)} hexes)`);
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console.log(` 5 Meilen/Hex → hexSize: 20 (~${Math.round(actualW/40)}×${Math.round(actualH/35)} hexes)`);
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}
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const [tilesDir, outputPath] = process.argv.slice(2);
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if (!tilesDir || !outputPath) {
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console.error('Usage: npx tsx pipeline/assemble-map.ts <tiles-dir> <output-image>');
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process.exit(1);
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}
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assembleTiles(resolve(tilesDir), resolve(outputPath)).catch(err => {
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console.error('Failed:', err);
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process.exit(1);
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});
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