2022-06-11 16:12:06 -05:00
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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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2022-06-19 08:16:35 -05:00
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import ffmpeg from 'fluent-ffmpeg';
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2022-06-30 20:43:33 -05:00
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import path from 'path';
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2022-07-02 21:06:36 -05:00
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import {
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IExifExtractionProcessor,
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IVideoLengthExtractionProcessor,
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exifExtractionProcessorName,
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imageTaggingProcessorName,
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objectDetectionProcessorName,
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2022-07-04 13:44:43 -05:00
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videoMetadataExtractionProcessorName,
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2022-07-02 21:06:36 -05:00
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metadataExtractionQueueName,
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} from '@app/job';
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@Processor(metadataExtractionQueueName)
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2022-06-11 16:12:06 -05:00
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export class MetadataExtractionProcessor {
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2022-06-25 19:53:06 +02:00
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private geocodingClient?: GeocodeService;
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2022-06-11 16:12:06 -05:00
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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 == 'true' && process.env.MAPBOX_KEY) {
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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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2022-07-02 21:06:36 -05:00
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@Process(exifExtractionProcessorName)
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async extractExifInfo(job: Job<IExifExtractionProcessor>) {
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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 = path.parse(fileName).name || 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 (this.geocodingClient && 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 ${String(e)}`, 'extractExif');
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}
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}
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2022-07-02 21:06:36 -05:00
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@Process({ name: imageTaggingProcessorName, concurrency: 2 })
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async tagImage(job: Job) {
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const { asset }: { asset: AssetEntity } = job.data;
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2022-07-01 16:20:04 +01:00
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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: objectDetectionProcessorName, 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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2022-07-01 16:20:04 +01:00
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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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2022-06-19 08:16:35 -05:00
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2022-07-04 13:44:43 -05:00
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@Process({ name: videoMetadataExtractionProcessorName, concurrency: 2 })
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async extractVideoMetadata(job: Job<IVideoLengthExtractionProcessor>) {
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const { asset } = job.data;
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ffmpeg.ffprobe(asset.originalPath, async (err, data) => {
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if (!err) {
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let durationString = asset.duration;
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let createdAt = asset.createdAt;
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if (data.format.duration) {
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durationString = this.extractDuration(data.format.duration);
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}
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const videoTags = data.format.tags;
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if (videoTags) {
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if (videoTags['com.apple.quicktime.creationdate']) {
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createdAt = String(videoTags['com.apple.quicktime.creationdate']);
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} else {
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createdAt = String(videoTags['creation_time']);
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}
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}
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await this.assetRepository.update({ id: asset.id }, { duration: durationString, createdAt: createdAt });
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}
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});
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}
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private extractDuration(duration: number) {
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const videoDurationInSecond = parseInt(duration.toString(), 0);
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const hours = Math.floor(videoDurationInSecond / 3600);
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const minutes = Math.floor((videoDurationInSecond - hours * 3600) / 60);
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const seconds = videoDurationInSecond - hours * 3600 - minutes * 60;
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return `${hours}:${minutes < 10 ? '0' + minutes.toString() : minutes}:${
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seconds < 10 ? '0' + seconds.toString() : seconds
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}.000000`;
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}
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}
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