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https://github.com/KevinMidboe/immich.git
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WIP refactor container and queuing system (#206)
* refactor microservices to machine-learning * Update tGithub issue template with correct task syntax * Added microservices container * Communicate between service based on queue system * added dependency * Fixed problem with having to import BullQueue into the individual service * Added todo * refactor server into monorepo with microservices * refactor database and entity to library * added simple migration * Move migrations and database config to library * Migration works in library * Cosmetic change in logging message * added user dto * Fixed issue with testing not able to find the shared library * Clean up library mapping path * Added webp generator to microservices * Update Github Action build latest * Fixed issue NPM cannot install due to conflict witl Bull Queue * format project with prettier * Modified docker-compose file * Add GH Action for Staging build: * Fixed GH action job name * Modified GH Action to only build & push latest when pushing to main * Added Test 2e2 Github Action * Added Test 2e2 Github Action * Implemented microservice to extract exif * Added cronjob to scan and generate webp thumbnail at midnight * Refactor to ireduce hit time to database when running microservices * Added error handling to asset services that handle read file from disk * Added video transcoding queue to process one video at a time * Fixed loading spinner on web while loading covering the info panel * Add mechanism to show new release announcement to web and mobile app (#209) * Added changelog page * Fixed issues based on PR comments * Fixed issue with video transcoding run on the server * Change entry point content for backward combatibility when starting up server * Added announcement box * Added error handling to failed silently when the app version checking is not able to make the request to GITHUB * Added new version announcement overlay * Update message * Added messages * Added logic to check and show announcement * Add method to handle saving new version * Added button to dimiss the acknowledge message * Up version for deployment to the app store
This commit is contained in:
Alex
GitHub
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import { Process, Processor } from '@nestjs/bull';
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import { Job } from 'bull';
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import { AssetEntity } from '@app/database/entities/asset.entity';
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import { Repository } from 'typeorm/repository/Repository';
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import { InjectRepository } from '@nestjs/typeorm';
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import { ExifEntity } from '@app/database/entities/exif.entity';
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import exifr from 'exifr';
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import mapboxGeocoding, { GeocodeService } from '@mapbox/mapbox-sdk/services/geocoding';
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import { MapiResponse } from '@mapbox/mapbox-sdk/lib/classes/mapi-response';
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import { readFile } from 'fs/promises';
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import { Logger } from '@nestjs/common';
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import axios from 'axios';
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import { SmartInfoEntity } from '@app/database/entities/smart-info.entity';
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@Processor('metadata-extraction-queue')
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export class MetadataExtractionProcessor {
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private geocodingClient: GeocodeService;
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constructor(
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@InjectRepository(AssetEntity)
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private assetRepository: Repository<AssetEntity>,
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@InjectRepository(ExifEntity)
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private exifRepository: Repository<ExifEntity>,
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@InjectRepository(SmartInfoEntity)
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private smartInfoRepository: Repository<SmartInfoEntity>,
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) {
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if (process.env.ENABLE_MAPBOX) {
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this.geocodingClient = mapboxGeocoding({
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accessToken: process.env.MAPBOX_KEY,
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});
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}
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}
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@Process('exif-extraction')
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async extractExifInfo(job: Job) {
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try {
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const { asset, fileName, fileSize }: { asset: AssetEntity; fileName: string; fileSize: number } = job.data;
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const fileBuffer = await readFile(asset.originalPath);
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const exifData = await exifr.parse(fileBuffer);
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const newExif = new ExifEntity();
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newExif.assetId = asset.id;
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newExif.make = exifData['Make'] || null;
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newExif.model = exifData['Model'] || null;
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newExif.imageName = fileName || null;
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newExif.exifImageHeight = exifData['ExifImageHeight'] || null;
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newExif.exifImageWidth = exifData['ExifImageWidth'] || null;
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newExif.fileSizeInByte = fileSize || null;
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newExif.orientation = exifData['Orientation'] || null;
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newExif.dateTimeOriginal = exifData['DateTimeOriginal'] || null;
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newExif.modifyDate = exifData['ModifyDate'] || null;
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newExif.lensModel = exifData['LensModel'] || null;
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newExif.fNumber = exifData['FNumber'] || null;
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newExif.focalLength = exifData['FocalLength'] || null;
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newExif.iso = exifData['ISO'] || null;
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newExif.exposureTime = exifData['ExposureTime'] || null;
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newExif.latitude = exifData['latitude'] || null;
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newExif.longitude = exifData['longitude'] || null;
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// Reverse GeoCoding
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if (process.env.ENABLE_MAPBOX && exifData['longitude'] && exifData['latitude']) {
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const geoCodeInfo: MapiResponse = await this.geocodingClient
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.reverseGeocode({
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query: [exifData['longitude'], exifData['latitude']],
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types: ['country', 'region', 'place'],
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})
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.send();
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const res: [] = geoCodeInfo.body['features'];
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const city = res.filter((geoInfo) => geoInfo['place_type'][0] == 'place')[0]['text'];
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const state = res.filter((geoInfo) => geoInfo['place_type'][0] == 'region')[0]['text'];
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const country = res.filter((geoInfo) => geoInfo['place_type'][0] == 'country')[0]['text'];
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newExif.city = city || null;
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newExif.state = state || null;
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newExif.country = country || null;
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}
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await this.exifRepository.save(newExif);
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} catch (e) {
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Logger.error(`Error extracting EXIF ${e.toString()}`, 'extractExif');
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}
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}
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@Process({ name: 'tag-image', concurrency: 2 })
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async tagImage(job: Job) {
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const { asset }: { asset: AssetEntity } = job.data;
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const res = await axios.post('http://immich-machine-learning:3001/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: 'detect-object', concurrency: 2 })
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async detectObject(job: Job) {
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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:3001/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 ${error.toString()}`);
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}
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}
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}
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