mirror of
https://github.com/snapotter-hq/SnapOtter.git
synced 2026-08-03 07:46:42 +02:00
test: expand coverage across all layers -- 1,268 new tests, fix replace-color div-by-zero
14-agent parallel test expansion covering integration, unit, E2E, E2E-Docker, cross-format matrix, adversarial, GUI navigation/tools/settings/visual/a11y/perf. - Integration: expand 23 tool test files with HEIC, stress, batch, edge cases - Unit: close coverage gaps in image-engine, stores, lib (metadata, auto-enhance, connection-store, lazy-with-retry, collage/file-store HEIC preview) - AI bridge: 141 new tests for dispatcher buffering, crash recovery, OOM/segfault - Cross-format: 794 parameterized tests (16 formats x 12 tools + no-crash matrix) - Adversarial: memory stress (50x large file), zero-byte, corrupted headers, unicode - E2E-Docker: expand 8 spec files with dimension verification, pipeline chains - GUI E2E: tool UI settings/interactions for all 47 tools, remove all test.skip, RBAC per-role verification, visual screenshot naming, cross-browser smoke tests, a11y ARIA/focus/contrast, performance budgets, 15-tool stability test - Fix: replace-color.ts tolerance=0 caused division-by-zero producing NaN pixels Total: 8,958 tests passing across 202 files. Zero failures, zero skips.
This commit is contained in:
SnapOtter
@@ -995,3 +995,257 @@ describe("Deep Enhance", () => {
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expect(result.downloadUrl).toBeDefined();
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});
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});
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// ── Darkening regression test ──────────────────────────────────
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describe("Darkening regression", () => {
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it("does not darken image at default intensity", async () => {
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// Create a known mid-brightness image
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const midGray = await sharp({
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create: {
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width: 100,
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height: 100,
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channels: 3,
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background: { r: 128, g: 128, b: 128 },
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},
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})
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.jpeg()
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.toBuffer();
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const originalStats = await sharp(midGray).stats();
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const originalMean =
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originalStats.channels[0].mean * 0.299 +
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originalStats.channels[1].mean * 0.587 +
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originalStats.channels[2].mean * 0.114;
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const res = await postTool(
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{ mode: "auto", intensity: 50 },
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midGray,
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"midgray.jpg",
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"image/jpeg",
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);
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expect(res.statusCode).toBe(200);
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const result = JSON.parse(res.body);
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const dlRes = await app.inject({
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method: "GET",
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url: result.downloadUrl,
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headers: { authorization: `Bearer ${adminToken}` },
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});
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const enhancedStats = await sharp(dlRes.rawPayload).stats();
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const enhancedMean =
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enhancedStats.channels[0].mean * 0.299 +
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enhancedStats.channels[1].mean * 0.587 +
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enhancedStats.channels[2].mean * 0.114;
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// The enhanced image should not lose more than 30% brightness
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// (regression: older versions would darken images dramatically)
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expect(enhancedMean).toBeGreaterThan(originalMean * 0.7);
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});
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it("does not darken a bright image", async () => {
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const bright = await sharp({
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create: {
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width: 100,
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height: 100,
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channels: 3,
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background: { r: 220, g: 220, b: 220 },
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},
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})
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.jpeg()
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.toBuffer();
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const originalStats = await sharp(bright).stats();
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const originalMean = originalStats.channels[0].mean;
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const res = await postTool({ mode: "auto", intensity: 50 }, bright, "bright.jpg", "image/jpeg");
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expect(res.statusCode).toBe(200);
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const result = JSON.parse(res.body);
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const dlRes = await app.inject({
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method: "GET",
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url: result.downloadUrl,
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headers: { authorization: `Bearer ${adminToken}` },
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});
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const enhancedStats = await sharp(dlRes.rawPayload).stats();
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const enhancedMean = enhancedStats.channels[0].mean;
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// Bright images should not be darkened more than 25%
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expect(enhancedMean).toBeGreaterThan(originalMean * 0.75);
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});
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});
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// ── Portrait image enhancement ─────────────────────────────────
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describe("Portrait image enhancement", () => {
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it("enhances a real portrait image in portrait mode", async () => {
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const portrait = readFileSync(join(FIXTURES, "test-portrait.jpg"));
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const res = await postTool(
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{ mode: "portrait", intensity: 60 },
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portrait,
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"portrait.jpg",
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"image/jpeg",
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);
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expect(res.statusCode).toBe(200);
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const result = JSON.parse(res.body);
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expect(result.downloadUrl).toBeDefined();
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const dlRes = await app.inject({
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method: "GET",
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url: result.downloadUrl,
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headers: { authorization: `Bearer ${adminToken}` },
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});
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const meta = await sharp(dlRes.rawPayload).metadata();
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expect(meta.format).toBe("jpeg");
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expect(meta.width).toBeGreaterThan(0);
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expect(meta.height).toBeGreaterThan(0);
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});
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it("enhances portrait-color content image in landscape mode", async () => {
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const portraitColor = readFileSync(join(FIXTURES, "content", "portrait-color.jpg"));
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const res = await postTool(
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{ mode: "landscape", intensity: 70 },
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portraitColor,
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"portrait-color.jpg",
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"image/jpeg",
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);
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expect(res.statusCode).toBe(200);
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const result = JSON.parse(res.body);
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expect(result.processedSize).toBeGreaterThan(0);
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});
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});
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// ── Batch processing (5+ images) ───────────────────────────────
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describe("Batch processing", () => {
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it("batch processes 5+ images and returns a ZIP", async () => {
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const TINY = readFileSync(join(FIXTURES, "test-1x1.png"));
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const { body: payload, contentType } = createMultipartPayload([
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{ name: "file", filename: "a.png", contentType: "image/png", content: PNG },
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{ name: "file", filename: "b.jpg", contentType: "image/jpeg", content: JPG },
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{ name: "file", filename: "c.webp", contentType: "image/webp", content: WEBP },
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{ name: "file", filename: "d.png", contentType: "image/png", content: TINY },
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{ name: "file", filename: "e.jpg", contentType: "image/jpeg", content: JPG },
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{ name: "settings", content: JSON.stringify({ mode: "auto", intensity: 50 }) },
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]);
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const res = await app.inject({
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method: "POST",
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url: "/api/v1/tools/image-enhancement/batch",
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payload,
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headers: {
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"content-type": contentType,
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authorization: `Bearer ${adminToken}`,
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},
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});
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expect(res.statusCode).toBe(200);
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expect(res.headers["content-type"]).toBe("application/zip");
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const AdmZip = (await import("adm-zip")).default;
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const zip = new AdmZip(res.rawPayload);
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const entries = zip.getEntries();
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expect(entries.length).toBe(5);
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// Each entry should be a valid image with size > 0
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for (const entry of entries) {
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expect(entry.getData().length).toBeGreaterThan(0);
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}
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});
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it("batch returns 400 with no files", async () => {
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const { body: payload, contentType } = createMultipartPayload([
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{ name: "settings", content: JSON.stringify({ mode: "auto" }) },
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]);
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const res = await app.inject({
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method: "POST",
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url: "/api/v1/tools/image-enhancement/batch",
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payload,
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headers: {
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"content-type": contentType,
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authorization: `Bearer ${adminToken}`,
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},
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});
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expect(res.statusCode).toBe(400);
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});
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});
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// ── Analyze endpoint response structure ────────────────────────
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describe("Analyze endpoint response structure", () => {
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it("analysis returns scores and corrections objects", async () => {
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const { body: payload, contentType } = createMultipartPayload([
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{ name: "file", filename: "test.jpg", contentType: "image/jpeg", content: JPG },
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]);
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const res = await app.inject({
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method: "POST",
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url: "/api/v1/tools/image-enhancement/analyze",
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payload,
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headers: {
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"content-type": contentType,
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authorization: `Bearer ${adminToken}`,
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},
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});
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expect(res.statusCode).toBe(200);
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const result = JSON.parse(res.body);
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expect(result).toHaveProperty("scores");
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expect(result).toHaveProperty("corrections");
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expect(result).toHaveProperty("issues");
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expect(result).toHaveProperty("suggestedMode");
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// Scores should have expected fields
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expect(typeof result.scores.exposure).toBe("number");
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expect(typeof result.scores.contrast).toBe("number");
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expect(typeof result.scores.whiteBalance).toBe("number");
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expect(typeof result.scores.saturation).toBe("number");
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expect(typeof result.scores.sharpness).toBe("number");
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expect(typeof result.scores.noise).toBe("number");
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// Corrections should have expected fields
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expect(typeof result.corrections.brightness).toBe("number");
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expect(typeof result.corrections.contrast).toBe("number");
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expect(typeof result.corrections.temperature).toBe("number");
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expect(typeof result.corrections.saturation).toBe("number");
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expect(typeof result.corrections.sharpness).toBe("number");
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expect(typeof result.corrections.denoise).toBe("number");
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// Issues should be an array of strings
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expect(Array.isArray(result.issues)).toBe(true);
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// SuggestedMode should be a valid mode string
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expect(["auto", "portrait", "landscape", "low-light", "food", "document"]).toContain(
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result.suggestedMode,
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);
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});
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});
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// ── Low-light image detection ──────────────────────────────────
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describe("Low-light image analysis", () => {
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it("analysis suggests low-light mode for dark image", async () => {
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const dark = await sharp({
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create: {
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width: 100,
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height: 100,
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channels: 3,
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background: { r: 20, g: 20, b: 20 },
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},
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})
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.jpeg()
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.toBuffer();
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const { body: payload, contentType } = createMultipartPayload([
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{ name: "file", filename: "dark.jpg", contentType: "image/jpeg", content: dark },
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]);
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const res = await app.inject({
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method: "POST",
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url: "/api/v1/tools/image-enhancement/analyze",
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payload,
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headers: {
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"content-type": contentType,
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authorization: `Bearer ${adminToken}`,
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},
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});
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expect(res.statusCode).toBe(200);
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const result = JSON.parse(res.body);
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expect(result.suggestedMode).toBe("low-light");
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expect(result.issues).toContain("underexposed");
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});
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});
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