mirror of
https://github.com/immich-app/immich.git
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61 lines
2.1 KiB
TypeScript
61 lines
2.1 KiB
TypeScript
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import { AssetEntity } from '@app/database/entities/asset.entity';
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import { SmartInfoEntity } from '@app/database/entities/smart-info.entity';
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import { MachineLearningJobNameEnum, QueueNameEnum } from '@app/job';
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import { IMachineLearningJob } from '@app/job/interfaces/machine-learning.interface';
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import { Process, Processor } from '@nestjs/bull';
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import { Logger } from '@nestjs/common';
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import { InjectRepository } from '@nestjs/typeorm';
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import axios from 'axios';
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import { Job } from 'bull';
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import { Repository } from 'typeorm';
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@Processor(QueueNameEnum.MACHINE_LEARNING)
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export class MachineLearningProcessor {
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constructor(
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@InjectRepository(SmartInfoEntity)
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private smartInfoRepository: Repository<SmartInfoEntity>,
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) {}
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@Process({ name: MachineLearningJobNameEnum.IMAGE_TAGGING, concurrency: 2 })
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async tagImage(job: Job<IMachineLearningJob>) {
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const { asset } = job.data;
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const res = await axios.post('http://immich-machine-learning:3003/image-classifier/tag-image', {
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thumbnailPath: asset.resizePath,
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});
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if (res.status == 201 && res.data.length > 0) {
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const smartInfo = new SmartInfoEntity();
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smartInfo.assetId = asset.id;
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smartInfo.tags = [...res.data];
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await this.smartInfoRepository.upsert(smartInfo, {
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conflictPaths: ['assetId'],
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});
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}
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}
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@Process({ name: MachineLearningJobNameEnum.OBJECT_DETECTION, concurrency: 2 })
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async detectObject(job: Job<IMachineLearningJob>) {
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try {
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const { asset }: { asset: AssetEntity } = job.data;
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const res = await axios.post('http://immich-machine-learning:3003/object-detection/detect-object', {
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thumbnailPath: asset.resizePath,
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});
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if (res.status == 201 && res.data.length > 0) {
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const smartInfo = new SmartInfoEntity();
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smartInfo.assetId = asset.id;
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smartInfo.objects = [...res.data];
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await this.smartInfoRepository.upsert(smartInfo, {
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conflictPaths: ['assetId'],
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});
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}
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} catch (error) {
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Logger.error(`Failed to trigger object detection pipe line ${String(error)}`);
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}
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}
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}
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