mirror of
https://github.com/sim1222/misskey.git
synced 2025-08-07 01:04:03 +09:00
feat: auto nsfw detection (#8840)
* feat: auto nsfw detection * ✌️ * Update ja-JP.yml * Update ja-JP.yml * ポルノ判定のしきい値を高めに * エラーハンドリングちゃんとした * Update ja-JP.yml * 感度設定を強化 * refactor * feat: add video support for auto nsfw detection * rename: image -> media * .js * fix: add missing error handling * fix: use valid pathname instead of using filename due to invalid usage * perf(nsfw-detection): decode frames * disable detection of video for some reasons * perf(nsfw-detection): streamify detection process for video * disable disallowUploadWhenPredictedAsPorn option * fix(nsfw-detection): improve reliability * fix(nsfw-detection): use Math.ceil instead of Math.round * perf(nsfw-detection): delete tmp frames after used * fix(nsfw-detection): FSWatcher does not emit ready event * perf(nsfw-detection): skip black frames * refactor: strip exists check * Update package.json * めっちゃ変えた * lint * Update COPYING * オプションで動画解析できるように * Update yarn.lock * Update CHANGELOG.md Co-authored-by: Acid Chicken (硫酸鶏) <root@acid-chicken.com>
This commit is contained in:
syuilo
GitHub
@ -1,12 +1,18 @@
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import * as fs from 'node:fs';
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import * as crypto from 'node:crypto';
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import { join } from 'node:path';
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import * as stream from 'node:stream';
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import * as util from 'node:util';
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import { FSWatcher } from 'chokidar';
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import { fileTypeFromFile } from 'file-type';
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import FFmpeg from 'fluent-ffmpeg';
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import isSvg from 'is-svg';
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import probeImageSize from 'probe-image-size';
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import { type predictionType } from 'nsfwjs';
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import sharp from 'sharp';
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import { encode } from 'blurhash';
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import { detectSensitive } from '@/services/detect-sensitive.js';
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import { createTempDir } from './create-temp.js';
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const pipeline = util.promisify(stream.pipeline);
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@ -21,6 +27,8 @@ export type FileInfo = {
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height?: number;
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orientation?: number;
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blurhash?: string;
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sensitive: boolean;
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porn: boolean;
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warnings: string[];
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};
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@ -37,7 +45,12 @@ const TYPE_SVG = {
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/**
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* Get file information
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*/
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export async function getFileInfo(path: string): Promise<FileInfo> {
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export async function getFileInfo(path: string, opts: {
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skipSensitiveDetection: boolean;
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sensitiveThreshold?: number;
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sensitiveThresholdForPorn?: number;
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enableSensitiveMediaDetectionForVideos?: boolean;
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}): Promise<FileInfo> {
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const warnings = [] as string[];
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const size = await getFileSize(path);
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@ -58,7 +71,7 @@ export async function getFileInfo(path: string): Promise<FileInfo> {
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// うまく判定できない画像は octet-stream にする
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if (!imageSize) {
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warnings.push(`cannot detect image dimensions`);
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warnings.push('cannot detect image dimensions');
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type = TYPE_OCTET_STREAM;
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} else if (imageSize.wUnits === 'px') {
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width = imageSize.width;
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@ -67,7 +80,7 @@ export async function getFileInfo(path: string): Promise<FileInfo> {
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// 制限を超えている画像は octet-stream にする
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if (imageSize.width > 16383 || imageSize.height > 16383) {
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warnings.push(`image dimensions exceeds limits`);
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warnings.push('image dimensions exceeds limits');
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type = TYPE_OCTET_STREAM;
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}
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} else {
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@ -84,6 +97,19 @@ export async function getFileInfo(path: string): Promise<FileInfo> {
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});
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}
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let sensitive = false;
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let porn = false;
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if (!opts.skipSensitiveDetection) {
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[sensitive, porn] = await detectSensitivity(
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path,
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type.mime,
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opts.sensitiveThreshold ?? 0.5,
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opts.sensitiveThresholdForPorn ?? 0.75,
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opts.enableSensitiveMediaDetectionForVideos ?? false,
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);
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}
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return {
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size,
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md5,
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@ -92,10 +118,150 @@ export async function getFileInfo(path: string): Promise<FileInfo> {
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height,
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orientation,
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blurhash,
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sensitive,
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porn,
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warnings,
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};
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}
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async function detectSensitivity(source: string, mime: string, sensitiveThreshold: number, sensitiveThresholdForPorn: number, analyzeVideo: boolean): Promise<[sensitive: boolean, porn: boolean]> {
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let sensitive = false;
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let porn = false;
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function judgePrediction(result: readonly predictionType[]): [sensitive: boolean, porn: boolean] {
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let sensitive = false;
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let porn = false;
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if ((result.find(x => x.className === 'Sexy')?.probability ?? 0) > sensitiveThreshold) sensitive = true;
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if ((result.find(x => x.className === 'Hentai')?.probability ?? 0) > sensitiveThreshold) sensitive = true;
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if ((result.find(x => x.className === 'Porn')?.probability ?? 0) > sensitiveThreshold) sensitive = true;
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if ((result.find(x => x.className === 'Porn')?.probability ?? 0) > sensitiveThresholdForPorn) porn = true;
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return [sensitive, porn];
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}
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if (['image/jpeg', 'image/png', 'image/webp'].includes(mime)) {
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const result = await detectSensitive(source);
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if (result) {
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[sensitive, porn] = judgePrediction(result);
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}
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} else if (analyzeVideo && (mime === 'image/apng' || mime.startsWith('video/'))) {
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const [outDir, disposeOutDir] = await createTempDir();
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try {
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const command = FFmpeg()
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.input(source)
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.inputOptions([
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'-skip_frame', 'nokey', // 可能ならキーフレームのみを取得してほしいとする（そうなるとは限らない）
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'-lowres', '3', // 元の画質でデコードする必要はないので 1/8 画質でデコードしてもよいとする（そうなるとは限らない）
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])
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.noAudio()
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.videoFilters([
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{
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filter: 'select', // フレームのフィルタリング
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options: {
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e: 'eq(pict_type,PICT_TYPE_I)', // I-Frame のみをフィルタする（VP9 とかはデコードしてみないとわからないっぽい）
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},
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},
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{
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filter: 'blackframe', // 暗いフレームの検出
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options: {
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amount: '0', // 暗さに関わらず全てのフレームで測定値を取る
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},
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},
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{
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filter: 'metadata',
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options: {
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mode: 'select', // フレーム選択モード
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key: 'lavfi.blackframe.pblack', // フレームにおける暗部の百分率（前のフィルタからのメタデータを参照する）
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value: '50',
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function: 'less', // 50% 未満のフレームを選択する（50% 以上暗部があるフレームだと誤検知を招くかもしれないので）
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},
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},
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{
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filter: 'scale',
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options: {
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w: 299,
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h: 299,
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},
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},
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])
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.format('image2')
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.output(join(outDir, '%d.png'))
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.outputOptions(['-vsync', '0']); // 可変フレームレートにすることで穴埋めをさせない
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const results: ReturnType<typeof judgePrediction>[] = [];
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let frameIndex = 0;
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let targetIndex = 0;
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let nextIndex = 1;
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for await (const path of asyncIterateFrames(outDir, command)) {
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try {
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const index = frameIndex++;
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if (index !== targetIndex) {
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continue;
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}
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targetIndex = nextIndex;
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nextIndex += index; // fibonacci sequence によってフレーム数制限を掛ける
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const result = await detectSensitive(path);
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if (result) {
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results.push(judgePrediction(result));
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}
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} finally {
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fs.promises.unlink(path);
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}
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}
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sensitive = results.filter(x => x[0]).length >= Math.ceil(results.length * sensitiveThreshold);
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porn = results.filter(x => x[1]).length >= Math.ceil(results.length * sensitiveThresholdForPorn);
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} finally {
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disposeOutDir();
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}
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}
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return [sensitive, porn];
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}
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async function* asyncIterateFrames(cwd: string, command: FFmpeg.FfmpegCommand): AsyncGenerator<string, void> {
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const watcher = new FSWatcher({
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cwd,
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disableGlobbing: true,
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});
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let finished = false;
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command.once('end', () => {
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finished = true;
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watcher.close();
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});
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command.run();
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for (let i = 1; true; i++) { // eslint-disable-line @typescript-eslint/no-unnecessary-condition
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const current = `${i}.png`;
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const next = `${i + 1}.png`;
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const framePath = join(cwd, current);
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if (await exists(join(cwd, next))) {
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yield framePath;
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} else if (!finished) { // eslint-disable-line @typescript-eslint/no-unnecessary-condition
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watcher.add(next);
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await new Promise<void>((resolve, reject) => {
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watcher.on('add', function onAdd(path) {
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if (path === next) { // 次フレームの書き出しが始まっているなら、現在フレームの書き出しは終わっている
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watcher.unwatch(current);
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watcher.off('add', onAdd);
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resolve();
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}
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});
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command.once('end', resolve); // 全てのフレームを処理し終わったなら、最終フレームである現在フレームの書き出しは終わっている
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command.once('error', reject);
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});
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yield framePath;
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} else if (await exists(framePath)) {
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yield framePath;
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} else {
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return;
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}
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}
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}
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function exists(path: string): Promise<boolean> {
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return fs.promises.access(path).then(() => true, () => false);
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}
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/**
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* Detect MIME Type and extension
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*/
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