mirror of
https://github.com/snapotter-hq/SnapOtter.git
synced 2026-08-03 07:46:42 +02:00
* feat(noise-removal): register tool in shared constants and i18n * feat(noise-removal): add SCUNet and NAFNet model architectures * feat(noise-removal): add Python denoising engine with 4 quality tiers * feat(noise-removal): add TypeScript bridge for Python sidecar * feat(noise-removal): add frontend settings with 4-tier selector * feat(noise-removal): register in tool registry and pipeline * feat(noise-removal): add Fastify API route with Zod validation * feat(noise-removal): add SCUNet and NAFNet model downloads to Docker build * test(noise-removal): add to e2e tool page rendering tests * test(noise-removal): add integration tests for API endpoint * style: fix biome formatting and import ordering * fix(noise-removal): use correct model download URLs NAFNet model is hosted on HuggingFace, not GitHub releases. Also align SCUNet URL to use the KAIR releases (same as Docker build). * fix(noise-removal): remove emojis from tier selector, simplify labels Drop emoji icons from Quick/Balanced/Quality/Maximum buttons. Replace technical algorithm names with plain descriptions users can understand. --------- Co-authored-by: stirling-image <stirling-image@users.noreply.github.com>
53 lines
1.3 KiB
TypeScript
53 lines
1.3 KiB
TypeScript
import { readFile, writeFile } from "node:fs/promises";
|
|
import { join } from "node:path";
|
|
import { type ProgressCallback, runPythonWithProgress } from "./bridge.js";
|
|
|
|
export interface NoiseRemovalOptions {
|
|
tier?: string;
|
|
strength?: number;
|
|
detailPreservation?: number;
|
|
colorNoise?: number;
|
|
format?: string;
|
|
quality?: number;
|
|
}
|
|
|
|
export interface NoiseRemovalResult {
|
|
buffer: Buffer;
|
|
width: number;
|
|
height: number;
|
|
format: string;
|
|
tier: string;
|
|
}
|
|
|
|
export async function noiseRemoval(
|
|
inputBuffer: Buffer,
|
|
outputDir: string,
|
|
options: NoiseRemovalOptions = {},
|
|
onProgress?: ProgressCallback,
|
|
): Promise<NoiseRemovalResult> {
|
|
const inputPath = join(outputDir, "input_denoise.png");
|
|
const outputPath = join(outputDir, "output_denoise.png");
|
|
|
|
await writeFile(inputPath, inputBuffer);
|
|
const { stdout } = await runPythonWithProgress(
|
|
"noise_removal.py",
|
|
[inputPath, outputPath, JSON.stringify(options)],
|
|
{ onProgress },
|
|
);
|
|
|
|
const result = JSON.parse(stdout);
|
|
if (!result.success) {
|
|
throw new Error(result.error || "Noise removal failed");
|
|
}
|
|
|
|
const actualOutputPath = result.output_path || outputPath;
|
|
const buffer = await readFile(actualOutputPath);
|
|
return {
|
|
buffer,
|
|
width: result.width,
|
|
height: result.height,
|
|
format: result.format ?? "png",
|
|
tier: result.tier ?? options.tier ?? "balanced",
|
|
};
|
|
}
|