test: add real-photo fixture harness for detection regressions
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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import { readFileSync } from 'node:fs';
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import { fileURLToPath } from 'node:url';
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import jpeg from 'jpeg-js';
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import { beforeAll, describe, expect, it } from 'vitest';
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import { detect, otsuThreshold } from '../src/lib/detect';
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import { prepareForExport, shapeSize } from '../src/lib/geometry';
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import { loadOpenCV, type CV } from '../src/lib/opencv-loader';
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import type { Point, RasterImage } from '../src/lib/types';
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type FixtureCase = {
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file: string;
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threshold: number | null;
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invert: boolean;
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seed: Point | null;
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pxPerMm: number;
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expected: { widthMm: number; heightMm: number; holes: number };
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toleranceMm: number;
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};
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const dir = fileURLToPath(new URL('./fixtures/', import.meta.url));
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const cases: FixtureCase[] = JSON.parse(readFileSync(dir + 'manifest.json', 'utf8'));
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function readJpeg(path: string): RasterImage {
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const decoded = jpeg.decode(readFileSync(path), { useTArray: true, formatAsRGBA: true });
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return { width: decoded.width, height: decoded.height, data: new Uint8ClampedArray(decoded.data) };
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}
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describe.skipIf(cases.length === 0)('detect on real photos', () => {
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let cv: CV;
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beforeAll(async () => {
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({ cv } = await loadOpenCV());
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});
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it.each(cases)('$file', (c) => {
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const image = readJpeg(dir + c.file);
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const threshold = c.threshold ?? otsuThreshold(cv, image);
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const shape = detect(cv, image, { threshold, invert: c.invert, seed: c.seed, marginPx: 0 });
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expect(shape).not.toBeNull();
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const mm = prepareForExport(shape!, c.pxPerMm)!;
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const size = shapeSize(mm);
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expect(Math.abs(size.width - c.expected.widthMm)).toBeLessThanOrEqual(c.toleranceMm);
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expect(Math.abs(size.height - c.expected.heightMm)).toBeLessThanOrEqual(c.toleranceMm);
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expect(mm.holes).toHaveLength(c.expected.holes);
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});
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});
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# Real photo fixtures
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Regression photos for `detect()`. Each entry in `manifest.json` is checked by `tests/fixtures.test.ts`.
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To add one:
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1. Take a top-down photo of a scrap piece with something of known length visible.
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2. Rotate it upright and resize it so the long side is at most 2000 px. Save as JPEG.
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EXIF orientation is ignored by the test decoder.
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3. Measure the real piece's bounding box in mm.
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4. Open the photo in the app, set the scale, and note px/mm, the threshold you used, and,
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if needed, a seed point (shown in image px).
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5. Add an entry:
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```json
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{
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"file": "plywood-1.jpg",
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"threshold": null,
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"invert": false,
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"seed": null,
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"pxPerMm": 3.21,
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"expected": { "widthMm": 412, "heightMm": 287, "holes": 2 },
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"toleranceMm": 8
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}
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```
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`threshold: null` means Otsu's automatic value. `seed` is `{ "x": ..., "y": ... }` or `null`.
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[]
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