417 lines
11 KiB
TypeScript
417 lines
11 KiB
TypeScript
import * as fs from 'node:fs';
|
||
import * as crypto from 'node:crypto';
|
||
import { join } from 'node:path';
|
||
import * as stream from 'node:stream';
|
||
import * as util from 'node:util';
|
||
import { Inject, Injectable } from '@nestjs/common';
|
||
import { FSWatcher } from 'chokidar';
|
||
import { fileTypeFromFile } from 'file-type';
|
||
import FFmpeg from 'fluent-ffmpeg';
|
||
import isSvg from 'is-svg';
|
||
import probeImageSize from 'probe-image-size';
|
||
import { type predictionType } from 'nsfwjs';
|
||
import sharp from 'sharp';
|
||
import { encode } from 'blurhash';
|
||
import { createTempDir } from '@/misc/create-temp.js';
|
||
import { AiService } from '@/core/AiService.js';
|
||
import { bindThis } from '@/decorators.js';
|
||
|
||
const pipeline = util.promisify(stream.pipeline);
|
||
|
||
export type FileInfo = {
|
||
size: number;
|
||
md5: string;
|
||
type: {
|
||
mime: string;
|
||
ext: string | null;
|
||
};
|
||
width?: number;
|
||
height?: number;
|
||
orientation?: number;
|
||
blurhash?: string;
|
||
sensitive: boolean;
|
||
porn: boolean;
|
||
warnings: string[];
|
||
};
|
||
|
||
const TYPE_OCTET_STREAM = {
|
||
mime: 'application/octet-stream',
|
||
ext: null,
|
||
};
|
||
|
||
const TYPE_SVG = {
|
||
mime: 'image/svg+xml',
|
||
ext: 'svg',
|
||
};
|
||
|
||
@Injectable()
|
||
export class FileInfoService {
|
||
constructor(
|
||
private aiService: AiService,
|
||
) {
|
||
}
|
||
|
||
/**
|
||
* Get file information
|
||
*/
|
||
@bindThis
|
||
public async getFileInfo(path: string, opts: {
|
||
skipSensitiveDetection: boolean;
|
||
sensitiveThreshold?: number;
|
||
sensitiveThresholdForPorn?: number;
|
||
enableSensitiveMediaDetectionForVideos?: boolean;
|
||
}): Promise<FileInfo> {
|
||
const warnings = [] as string[];
|
||
|
||
const size = await this.getFileSize(path);
|
||
const md5 = await this.calcHash(path);
|
||
|
||
let type = await this.detectType(path);
|
||
|
||
// image dimensions
|
||
let width: number | undefined;
|
||
let height: number | undefined;
|
||
let orientation: number | undefined;
|
||
|
||
if ([
|
||
'image/png',
|
||
'image/gif',
|
||
'image/jpeg',
|
||
'image/webp',
|
||
'image/avif',
|
||
'image/apng',
|
||
'image/bmp',
|
||
'image/tiff',
|
||
'image/svg+xml',
|
||
'image/vnd.adobe.photoshop',
|
||
].includes(type.mime)) {
|
||
const imageSize = await this.detectImageSize(path).catch(e => {
|
||
warnings.push(`detectImageSize failed: ${e}`);
|
||
return undefined;
|
||
});
|
||
|
||
// うまく判定できない画像は octet-stream にする
|
||
if (!imageSize) {
|
||
warnings.push('cannot detect image dimensions');
|
||
type = TYPE_OCTET_STREAM;
|
||
} else if (imageSize.wUnits === 'px') {
|
||
width = imageSize.width;
|
||
height = imageSize.height;
|
||
orientation = imageSize.orientation;
|
||
|
||
// 制限を超えている画像は octet-stream にする
|
||
if (imageSize.width > 16383 || imageSize.height > 16383) {
|
||
warnings.push('image dimensions exceeds limits');
|
||
type = TYPE_OCTET_STREAM;
|
||
}
|
||
} else {
|
||
warnings.push(`unsupported unit type: ${imageSize.wUnits}`);
|
||
}
|
||
}
|
||
|
||
let blurhash: string | undefined;
|
||
|
||
if ([
|
||
'image/jpeg',
|
||
'image/gif',
|
||
'image/png',
|
||
'image/apng',
|
||
'image/webp',
|
||
'image/avif',
|
||
'image/svg+xml',
|
||
].includes(type.mime)) {
|
||
blurhash = await this.getBlurhash(path).catch(e => {
|
||
warnings.push(`getBlurhash failed: ${e}`);
|
||
return undefined;
|
||
});
|
||
}
|
||
|
||
let sensitive = false;
|
||
let porn = false;
|
||
|
||
if (!opts.skipSensitiveDetection) {
|
||
await this.detectSensitivity(
|
||
path,
|
||
type.mime,
|
||
opts.sensitiveThreshold ?? 0.5,
|
||
opts.sensitiveThresholdForPorn ?? 0.75,
|
||
opts.enableSensitiveMediaDetectionForVideos ?? false,
|
||
).then(value => {
|
||
[sensitive, porn] = value;
|
||
}, error => {
|
||
warnings.push(`detectSensitivity failed: ${error}`);
|
||
});
|
||
}
|
||
|
||
return {
|
||
size,
|
||
md5,
|
||
type,
|
||
width,
|
||
height,
|
||
orientation,
|
||
blurhash,
|
||
sensitive,
|
||
porn,
|
||
warnings,
|
||
};
|
||
}
|
||
|
||
@bindThis
|
||
private async detectSensitivity(source: string, mime: string, sensitiveThreshold: number, sensitiveThresholdForPorn: number, analyzeVideo: boolean): Promise<[sensitive: boolean, porn: boolean]> {
|
||
let sensitive = false;
|
||
let porn = false;
|
||
|
||
function judgePrediction(result: readonly predictionType[]): [sensitive: boolean, porn: boolean] {
|
||
let sensitive = false;
|
||
let porn = false;
|
||
|
||
if ((result.find(x => x.className === 'Sexy')?.probability ?? 0) > sensitiveThreshold) sensitive = true;
|
||
if ((result.find(x => x.className === 'Hentai')?.probability ?? 0) > sensitiveThreshold) sensitive = true;
|
||
if ((result.find(x => x.className === 'Porn')?.probability ?? 0) > sensitiveThreshold) sensitive = true;
|
||
|
||
if ((result.find(x => x.className === 'Porn')?.probability ?? 0) > sensitiveThresholdForPorn) porn = true;
|
||
|
||
return [sensitive, porn];
|
||
}
|
||
|
||
if ([
|
||
'image/jpeg',
|
||
'image/png',
|
||
'image/webp',
|
||
].includes(mime)) {
|
||
const result = await this.aiService.detectSensitive(source);
|
||
if (result) {
|
||
[sensitive, porn] = judgePrediction(result);
|
||
}
|
||
} else if (analyzeVideo && (mime === 'image/apng' || mime.startsWith('video/'))) {
|
||
const [outDir, disposeOutDir] = await createTempDir();
|
||
try {
|
||
const command = FFmpeg()
|
||
.input(source)
|
||
.inputOptions([
|
||
'-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）
|
||
'-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）
|
||
])
|
||
.noAudio()
|
||
.videoFilters([
|
||
{
|
||
filter: 'select', // フレームのフィルタリング
|
||
options: {
|
||
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）
|
||
},
|
||
},
|
||
{
|
||
filter: 'blackframe', // 暗いフレームの検出
|
||
options: {
|
||
amount: '0', // 暗さに関わらず全てのフレームで測定値を取る
|
||
},
|
||
},
|
||
{
|
||
filter: 'metadata',
|
||
options: {
|
||
mode: 'select', // フレーム選択モード
|
||
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）
|
||
value: '50',
|
||
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）
|
||
},
|
||
},
|
||
{
|
||
filter: 'scale',
|
||
options: {
|
||
w: 299,
|
||
h: 299,
|
||
},
|
||
},
|
||
])
|
||
.format('image2')
|
||
.output(join(outDir, '%d.png'))
|
||
.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
|
||
const results: ReturnType<typeof judgePrediction>[] = [];
|
||
let frameIndex = 0;
|
||
let targetIndex = 0;
|
||
let nextIndex = 1;
|
||
for await (const path of this.asyncIterateFrames(outDir, command)) {
|
||
try {
|
||
const index = frameIndex++;
|
||
if (index !== targetIndex) {
|
||
continue;
|
||
}
|
||
targetIndex = nextIndex;
|
||
nextIndex += index; // fibonacci sequence によってフレーム数制限を掛ける
|
||
const result = await this.aiService.detectSensitive(path);
|
||
if (result) {
|
||
results.push(judgePrediction(result));
|
||
}
|
||
} finally {
|
||
fs.promises.unlink(path);
|
||
}
|
||
}
|
||
sensitive = results.filter(x => x[0]).length >= Math.ceil(results.length * sensitiveThreshold);
|
||
porn = results.filter(x => x[1]).length >= Math.ceil(results.length * sensitiveThresholdForPorn);
|
||
} finally {
|
||
disposeOutDir();
|
||
}
|
||
}
|
||
|
||
return [sensitive, porn];
|
||
}
|
||
|
||
private async *asyncIterateFrames(cwd: string, command: FFmpeg.FfmpegCommand): AsyncGenerator<string, void> {
|
||
const watcher = new FSWatcher({
|
||
cwd,
|
||
disableGlobbing: true,
|
||
});
|
||
let finished = false;
|
||
command.once('end', () => {
|
||
finished = true;
|
||
watcher.close();
|
||
});
|
||
command.run();
|
||
for (let i = 1; true; i++) { // eslint-disable-line @typescript-eslint/no-unnecessary-condition
|
||
const current = `${i}.png`;
|
||
const next = `${i + 1}.png`;
|
||
const framePath = join(cwd, current);
|
||
if (await this.exists(join(cwd, next))) {
|
||
yield framePath;
|
||
} else if (!finished) { // eslint-disable-line @typescript-eslint/no-unnecessary-condition
|
||
watcher.add(next);
|
||
await new Promise<void>((resolve, reject) => {
|
||
watcher.on('add', function onAdd(path) {
|
||
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
|
||
watcher.unwatch(current);
|
||
watcher.off('add', onAdd);
|
||
resolve();
|
||
}
|
||
});
|
||
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
|
||
command.once('error', reject);
|
||
});
|
||
yield framePath;
|
||
} else if (await this.exists(framePath)) {
|
||
yield framePath;
|
||
} else {
|
||
return;
|
||
}
|
||
}
|
||
}
|
||
|
||
@bindThis
|
||
private exists(path: string): Promise<boolean> {
|
||
return fs.promises.access(path).then(() => true, () => false);
|
||
}
|
||
|
||
/**
|
||
* Detect MIME Type and extension
|
||
*/
|
||
@bindThis
|
||
public async detectType(path: string): Promise<{
|
||
mime: string;
|
||
ext: string | null;
|
||
}> {
|
||
// Check 0 byte
|
||
const fileSize = await this.getFileSize(path);
|
||
if (fileSize === 0) {
|
||
return TYPE_OCTET_STREAM;
|
||
}
|
||
|
||
const type = await fileTypeFromFile(path);
|
||
|
||
if (type) {
|
||
// XMLはSVGかもしれない
|
||
if (type.mime === 'application/xml' && await this.checkSvg(path)) {
|
||
return TYPE_SVG;
|
||
}
|
||
|
||
return {
|
||
mime: type.mime,
|
||
ext: type.ext,
|
||
};
|
||
}
|
||
|
||
// 種類が不明でもSVGかもしれない
|
||
if (await this.checkSvg(path)) {
|
||
return TYPE_SVG;
|
||
}
|
||
|
||
// それでも種類が不明なら application/octet-stream にする
|
||
return TYPE_OCTET_STREAM;
|
||
}
|
||
|
||
/**
|
||
* Check the file is SVG or not
|
||
*/
|
||
@bindThis
|
||
public async checkSvg(path: string) {
|
||
try {
|
||
const size = await this.getFileSize(path);
|
||
if (size > 1 * 1024 * 1024) return false;
|
||
return isSvg(fs.readFileSync(path));
|
||
} catch {
|
||
return false;
|
||
}
|
||
}
|
||
|
||
/**
|
||
* Get file size
|
||
*/
|
||
@bindThis
|
||
public async getFileSize(path: string): Promise<number> {
|
||
const getStat = util.promisify(fs.stat);
|
||
return (await getStat(path)).size;
|
||
}
|
||
|
||
/**
|
||
* Calculate MD5 hash
|
||
*/
|
||
@bindThis
|
||
private async calcHash(path: string): Promise<string> {
|
||
const hash = crypto.createHash('md5').setEncoding('hex');
|
||
await pipeline(fs.createReadStream(path), hash);
|
||
return hash.read();
|
||
}
|
||
|
||
/**
|
||
* Detect dimensions of image
|
||
*/
|
||
@bindThis
|
||
private async detectImageSize(path: string): Promise<{
|
||
width: number;
|
||
height: number;
|
||
wUnits: string;
|
||
hUnits: string;
|
||
orientation?: number;
|
||
}> {
|
||
const readable = fs.createReadStream(path);
|
||
const imageSize = await probeImageSize(readable);
|
||
readable.destroy();
|
||
return imageSize;
|
||
}
|
||
|
||
/**
|
||
* Calculate average color of image
|
||
*/
|
||
@bindThis
|
||
private getBlurhash(path: string): Promise<string> {
|
||
return new Promise((resolve, reject) => {
|
||
sharp(path)
|
||
.raw()
|
||
.ensureAlpha()
|
||
.resize(64, 64, { fit: 'inside' })
|
||
.toBuffer((err, buffer, info) => {
|
||
if (err) return reject(err);
|
||
|
||
let hash;
|
||
|
||
try {
|
||
hash = encode(new Uint8ClampedArray(buffer), info.width, info.height, 5, 5);
|
||
} catch (e) {
|
||
return reject(e);
|
||
}
|
||
|
||
resolve(hash);
|
||
});
|
||
});
|
||
}
|
||
}
|