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import * as fs from 'node:fs';
import { fileURLToPath } from 'node:url';
import { dirname } from 'node:path';
import { Inject, Injectable } from '@nestjs/common';
import * as nsfw from 'nsfwjs';
import si from 'systeminformation';
import { Config } from '@/config.js';
import { DI } from '@/di-symbols.js';
const _filename = fileURLToPath(import.meta.url);
const _dirname = dirname(_filename);
const REQUIRED_CPU_FLAGS = ['avx2', 'fma'];
let isSupportedCpu: undefined | boolean = undefined;
@Injectable()
export class AiService {
#model: nsfw.NSFWJS;
constructor(
@Inject(DI.config)
private config: Config,
) {
}
public async detectSensitive(path: string): Promise<nsfw.predictionType[] | null> {
try {
if (isSupportedCpu === undefined) {
const cpuFlags = await this.#getCpuFlags();
isSupportedCpu = REQUIRED_CPU_FLAGS.every(required => cpuFlags.includes(required));
}
if (!isSupportedCpu) {
console.error('This CPU cannot use TensorFlow.');
return null;
}
const tf = await import('@tensorflow/tfjs-node');
if (this.#model == null) this.#model = await nsfw.load(`file://${_dirname}/../../nsfw-model/`, { size: 299 });
const buffer = await fs.promises.readFile(path);
const image = await tf.node.decodeImage(buffer, 3) as any;
try {
const predictions = await this.#model.classify(image);
return predictions;
} finally {
image.dispose();
}
} catch (err) {
console.error(err);
return null;
}
}
async #getCpuFlags(): Promise<string[]> {
const str = await si.cpuFlags();
return str.split(/\s+/);
}
}
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