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Support HEIC/HEIF (#16) 

* Support HEIC/HEIF backup
* Storing backup directly from original file from the phone
* Directly read and backup video file - Improve performance on video backup
pull/19/head
Alex 2022-02-09 20:48:06 +07:00 committed by GitHub
parent f578ca6d47
commit 38c968d47e
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GPG Key ID: 4AEE18F83AFDEB23
15 changed files with 254 additions and 234 deletions
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4
README.md
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@ -36,11 +36,13 @@ This project is under heavy development, there will be continous functions, feat
[x] Auto Backup
[x] Support HEIC
# Development
You can use docker compose for development, there are several services that compose Immich
1. The server
1. NestJs
2. PostgreSQL
3. Redis
4. Nginx

1
mobile/lib/modules/home/ui/thumbnail_image.dart
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@ -49,7 +49,6 @@ class ThumbnailImage extends HookConsumerWidget {
} else if (isMultiSelectEnable && !selectedAsset.contains(asset)) {
ref.watch(homePageStateProvider.notifier).addSingleSelectedItem(asset);
} else {
print(asset.id);
if (asset.type == 'IMAGE') {
AutoRouter.of(context).push(
ImageViewerRoute(

2
mobile/lib/modules/login/ui/login_form.dart
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@ -126,7 +126,7 @@ class LoginButton extends ConsumerWidget {
} else {
ImmichToast.show(
context: context,
msg: "Error logging you in, check server url, emald and password!",
msg: "Error logging you in, check server url, email and password!",
toastType: ToastType.error);
}
},

12
mobile/lib/shared/services/backup.service.dart
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@ -37,20 +37,12 @@ class BackupService {
for (var entity in assetList) {
try {
if (entity.type == AssetType.video) {
file = await entity.file;
file = await entity.originFile;
} else {
file = await entity.file.timeout(const Duration(seconds: 5));
file = await entity.originFile.timeout(const Duration(seconds: 5));
}
if (file != null) {
// reading exif
// var exifData = await readExifFromFile(file);
// for (String key in exifData.keys) {
// debugPrint("- $key (${exifData[key]?.tagType}): ${exifData[key]}");
// }
// debugPrint("------------------");
String originalFileName = await entity.titleAsync;
String fileNameWithoutPath = originalFileName.toString().split(".")[0];
var fileExtension = p.extension(file.path);

8
mobile/lib/utils/files_helper.dart
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@ -1,9 +1,7 @@
import 'package:flutter/material.dart';
import 'package:path/path.dart' as p;
class FileHelper {
static getMimeType(String filePath) {
debugPrint(filePath);
var fileExtension = p.extension(filePath).split(".")[1];
switch (fileExtension.toLowerCase()) {
@ -28,6 +26,12 @@ class FileHelper {
case 'avi':
return {"type": "video", "subType": "x-msvideo"};
case 'heic':
return {"type": "image", "subType": "heic"};
case 'heif':
return {"type": "image", "subType": "heif"};
default:
return {"type": "unsupport", "subType": "unsupport"};
}

9
mobile/pubspec.lock
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@ -513,6 +513,13 @@ packages:
url: "https://pub.dartlang.org"
source: hosted
version: "0.12.11"
material_color_utilities:
dependency: transitive
description:
name: material_color_utilities
url: "https://pub.dartlang.org"
source: hosted
version: "0.1.3"
meta:
dependency: transitive
description:
@ -818,7 +825,7 @@ packages:
name: test_api
url: "https://pub.dartlang.org"
source: hosted
version: "0.4.3"
version: "0.4.8"
timing:
dependency: transitive
description:

14
server/Dockerfile
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@ -1,7 +1,7 @@
##################################
# DEVELOPMENT
##################################
FROM node:16-bullseye-slim AS development
FROM node:16-alpine3.14 AS development
ARG DEBIAN_FRONTEND=noninteractive
@ -9,8 +9,7 @@ WORKDIR /usr/src/app
COPY package.json package-lock.json ./
RUN apt-get update
RUN apt-get install gcc g++ make cmake python3 python3-pip ffmpeg -y
RUN apk add --update-cache build-base python3 libheif vips-dev vips ffmpeg
RUN npm install
@ -18,15 +17,6 @@ COPY . .
RUN npm run build
# Clean up commands
RUN apt-get autoremove -y && apt-get clean && \
rm -rf /usr/local/src/*
RUN apt-get clean && \
rm -rf /var/lib/apt/lists/*
##################################
# PRODUCTION
##################################

316
server/package-lock.json generated
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@ -19,17 +19,13 @@
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"@nestjs/platform-fastify": "^8.2.6",
"@nestjs/typeorm": "^8.0.3",
"@tensorflow-models/coco-ssd": "^2.2.2",
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"@tensorflow/tfjs-converter": "^3.13.0",
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"class-transformer": "^0.5.1",
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"dotenv": "^14.2.0",
"fluent-ffmpeg": "^2.1.2",
"heic-convert": "^1.2.4",
"joi": "^17.5.0",
"lodash": "^4.17.21",
"passport": "^0.5.2",
@ -38,7 +34,7 @@
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"rimraf": "^3.0.2",
"rxjs": "^7.2.0",
"sharp": "^0.29.3",
"sharp": "0.28",
"systeminformation": "^5.11.0",
"typeorm": "^0.2.41"
},
@ -3723,12 +3719,12 @@
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@ -3756,6 +3752,19 @@
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@ -4069,17 +4078,14 @@
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@ -5650,6 +5656,30 @@
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}
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@ -6864,6 +6894,11 @@
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}
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@ -7076,6 +7111,14 @@
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}
},
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"resolved": "https://registry.npmjs.org/libheif-js/-/libheif-js-1.12.0.tgz",
"integrity": "sha512-hDs6xQ7028VOwAFwEtM0Q+B2x2NW69Jb2MhQFUbk3rUrHzz4qo5mqS8VrqNgYnSc8TiUGnR691LnO4uIfEE23w==",
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}
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@ -7419,11 +7462,11 @@
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"engines": {
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},
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@ -7574,14 +7617,19 @@
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@ -8196,6 +8244,14 @@
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@ -8232,21 +8288,21 @@
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@ -8254,15 +8310,7 @@
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@ -8922,32 +8970,27 @@
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"requires": {
"heic-decode": "^1.1.2",
"jpeg-js": "^0.4.1",
"pngjs": "^3.4.0"
}
},
"heic-decode": {
"version": "1.1.2",
"resolved": "https://registry.npmjs.org/heic-decode/-/heic-decode-1.1.2.tgz",
"integrity": "sha512-UF8teegxvzQPdSTcx5frIUhitNDliz/9Pui0JFdIqVRE00spVE33DcCYtZqaLNyd4y5RP/QQWZFIc1YWVKKm2A==",
"requires": {
"libheif-js": "^1.10.0"
}
},
"hexoid": {
"version": "1.0.0",
"resolved": "https://registry.npmjs.org/hexoid/-/hexoid-1.0.0.tgz",
@ -15922,6 +15984,11 @@
"@sideway/pinpoint": "^2.0.0"
}
},
"jpeg-js": {
"version": "0.4.3",
"resolved": "https://registry.npmjs.org/jpeg-js/-/jpeg-js-0.4.3.tgz",
"integrity": "sha512-ru1HWKek8octvUHFHvE5ZzQ1yAsJmIvRdGWvSoKV52XKyuyYA437QWDttXT8eZXDSbuMpHlLzPDZUPd6idIz+Q=="
},
"js-tokens": {
"version": "4.0.0",
"resolved": "https://registry.npmjs.org/js-tokens/-/js-tokens-4.0.0.tgz",
@ -16097,6 +16164,11 @@
"type-check": "~0.4.0"
}
},
"libheif-js": {
"version": "1.12.0",
"resolved": "https://registry.npmjs.org/libheif-js/-/libheif-js-1.12.0.tgz",
"integrity": "sha512-hDs6xQ7028VOwAFwEtM0Q+B2x2NW69Jb2MhQFUbk3rUrHzz4qo5mqS8VrqNgYnSc8TiUGnR691LnO4uIfEE23w=="
},
"libphonenumber-js": {
"version": "1.9.48",
"resolved": "https://registry.npmjs.org/libphonenumber-js/-/libphonenumber-js-1.9.48.tgz",
@ -16376,9 +16448,9 @@
"dev": true
},
"mimic-response": {
"version": "3.1.0",
"resolved": "https://registry.npmjs.org/mimic-response/-/mimic-response-3.1.0.tgz",
"integrity": "sha512-z0yWI+4FDrrweS8Zmt4Ej5HdJmky15+L2e6Wgn3+iK5fWzb6T3fhNFq2+MeTRb064c6Wr4N/wv0DzQTjNzHNGQ=="
"version": "2.1.0",
"resolved": "https://registry.npmjs.org/mimic-response/-/mimic-response-2.1.0.tgz",
"integrity": "sha512-wXqjST+SLt7R009ySCglWBCFpjUygmCIfD790/kVbiGmUgfYGuB14PiTd5DwVxSV4NcYHjzMkoj5LjQZwTQLEA=="
},
"minimatch": {
"version": "3.0.4",
@ -16506,11 +16578,18 @@
"dev": true
},
"node-abi": {
"version": "3.8.0",
"resolved": "https://registry.npmjs.org/node-abi/-/node-abi-3.8.0.tgz",
"integrity": "sha512-tzua9qWWi7iW4I42vUPKM+SfaF0vQSLAm4yO5J83mSwB7GeoWrDKC/K+8YCnYNwqP5duwazbw2X9l4m8SC2cUw==",
"version": "2.30.1",
"resolved": "https://registry.npmjs.org/node-abi/-/node-abi-2.30.1.tgz",
"integrity": "sha512-/2D0wOQPgaUWzVSVgRMx+trKJRC2UG4SUc4oCJoXx9Uxjtp0Vy3/kt7zcbxHF8+Z/pK3UloLWzBISg72brfy1w==",
"requires": {
"semver": "^7.3.5"
"semver": "^5.4.1"
},
"dependencies": {
"semver": {
"version": "5.7.1",
"resolved": "https://registry.npmjs.org/semver/-/semver-5.7.1.tgz",
"integrity": "sha512-sauaDf/PZdVgrLTNYHRtpXa1iRiKcaebiKQ1BJdpQlWH2lCvexQdX55snPFyK7QzpudqbCI0qXFfOasHdyNDGQ=="
}
}
},
"node-addon-api": {
@ -16968,6 +17047,11 @@
"integrity": "sha512-Nc3IT5yHzflTfbjgqWcCPpo7DaKy4FnpB0l/zCAW0Tc7jxAiuqSxHasntB3D7887LSrA93kDJ9IXovxJYxyLCA==",
"dev": true
},
"pngjs": {
"version": "3.4.0",
"resolved": "https://registry.npmjs.org/pngjs/-/pngjs-3.4.0.tgz",
"integrity": "sha512-NCrCHhWmnQklfH4MtJMRjZ2a8c80qXeMlQMv2uVp9ISJMTt562SbGd6n2oq0PaPgKm7Z6pL9E2UlLIhC+SHL3w=="
},
"postgres-array": {
"version": "2.0.0",
"resolved": "https://registry.npmjs.org/postgres-array/-/postgres-array-2.0.0.tgz",
@ -16992,30 +17076,23 @@
}
},
"prebuild-install": {
"version": "7.0.1",
"resolved": "https://registry.npmjs.org/prebuild-install/-/prebuild-install-7.0.1.tgz",
"integrity": "sha512-QBSab31WqkyxpnMWQxubYAHR5S9B2+r81ucocew34Fkl98FhvKIF50jIJnNOBmAZfyNV7vE5T6gd3hTVWgY6tg==",
"version": "6.1.4",
"resolved": "https://registry.npmjs.org/prebuild-install/-/prebuild-install-6.1.4.tgz",
"integrity": "sha512-Z4vpywnK1lBg+zdPCVCsKq0xO66eEV9rWo2zrROGGiRS4JtueBOdlB1FnY8lcy7JsUud/Q3ijUxyWN26Ika0vQ==",
"requires": {
"detect-libc": "^2.0.0",
"detect-libc": "^1.0.3",
"expand-template": "^2.0.3",
"github-from-package": "0.0.0",
"minimist": "^1.2.3",
"mkdirp-classic": "^0.5.3",
"napi-build-utils": "^1.0.1",
"node-abi": "^3.3.0",
"node-abi": "^2.21.0",
"npmlog": "^4.0.1",
"pump": "^3.0.0",
"rc": "^1.2.7",
"simple-get": "^4.0.0",
"simple-get": "^3.0.3",
"tar-fs": "^2.0.0",
"tunnel-agent": "^0.6.0"
},
"dependencies": {
"detect-libc": {
"version": "2.0.0",
"resolved": "https://registry.npmjs.org/detect-libc/-/detect-libc-2.0.0.tgz",
"integrity": "sha512-S55LzUl8HUav8l9E2PBTlC5PAJrHK7tkM+XXFGD+fbsbkTzhCpG6K05LxJcUOEWzMa4v6ptcMZ9s3fOdJDu0Zw=="
}
}
},
"prelude-ls": {
@ -17497,25 +17574,18 @@
}
},
"sharp": {
"version": "0.29.3",
"resolved": "https://registry.npmjs.org/sharp/-/sharp-0.29.3.tgz",
"integrity": "sha512-fKWUuOw77E4nhpyzCCJR1ayrttHoFHBT2U/kR/qEMRhvPEcluG4BKj324+SCO1e84+knXHwhJ1HHJGnUt4ElGA==",
"version": "0.28.3",
"resolved": "https://registry.npmjs.org/sharp/-/sharp-0.28.3.tgz",
"integrity": "sha512-21GEP45Rmr7q2qcmdnjDkNP04Ooh5v0laGS5FDpojOO84D1DJwUijLiSq8XNNM6e8aGXYtoYRh3sVNdm8NodMA==",
"requires": {
"color": "^4.0.1",
"color": "^3.1.3",
"detect-libc": "^1.0.3",
"node-addon-api": "^4.2.0",
"prebuild-install": "^7.0.0",
"node-addon-api": "^3.2.0",
"prebuild-install": "^6.1.2",
"semver": "^7.3.5",
"simple-get": "^4.0.0",
"simple-get": "^3.1.0",
"tar-fs": "^2.1.1",
"tunnel-agent": "^0.6.0"
},
"dependencies": {
"node-addon-api": {
"version": "4.3.0",
"resolved": "https://registry.npmjs.org/node-addon-api/-/node-addon-api-4.3.0.tgz",
"integrity": "sha512-73sE9+3UaLYYFmDsFZnqCInzPyh3MqIwZO9cw58yIqAZhONrrabrYyYe3TuIqtIiOuTXVhsGau8hcrhhwSsDIQ=="
}
}
},
"shebang-command": {
@ -17566,11 +17636,11 @@
"integrity": "sha512-cSFtAPtRhljv69IK0hTVZQ+OfE9nePi/rtJmw5UjHeVyVroEqJXP1sFztKUy1qU+xvz3u/sfYJLa947b7nAN2Q=="
},
"simple-get": {
"version": "4.0.1",
"resolved": "https://registry.npmjs.org/simple-get/-/simple-get-4.0.1.tgz",
"integrity": "sha512-brv7p5WgH0jmQJr1ZDDfKDOSeWWg+OVypG99A/5vYGPqJ6pxiaHLy8nxtFjBA7oMa01ebA9gfh1uMCFqOuXxvA==",
"version": "3.1.1",
"resolved": "https://registry.npmjs.org/simple-get/-/simple-get-3.1.1.tgz",
"integrity": "sha512-CQ5LTKGfCpvE1K0n2us+kuMPbk/q0EKl82s4aheV9oXjFEz6W/Y7oQFVJuU6QG77hRT4Ghb5RURteF5vnWjupA==",
"requires": {
"decompress-response": "^6.0.0",
"decompress-response": "^4.2.0",
"once": "^1.3.1",
"simple-concat": "^1.0.0"
}

2
server/package.json
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@ -50,7 +50,7 @@
"reflect-metadata": "^0.1.13",
"rimraf": "^3.0.2",
"rxjs": "^7.2.0",
"sharp": "^0.29.3",
"sharp": "0.28",
"systeminformation": "^5.11.0",
"typeorm": "^0.2.41"
},

8
server/src/api-v1/asset/asset.module.ts
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@ -17,14 +17,6 @@ import { BullModule } from '@nestjs/bull';
removeOnFail: false,
},
}),
BullModule.registerQueue({
name: 'machine-learning',
defaultJobOptions: {
attempts: 3,
removeOnComplete: true,
removeOnFail: false,
},
}),
TypeOrmModule.forFeature([AssetEntity]),
ImageOptimizeModule,
],

1
server/src/api-v1/asset/asset.service.ts
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@ -8,7 +8,6 @@ import { AssetEntity, AssetType } from './entities/asset.entity';
import _ from 'lodash';
import { GetAllAssetQueryDto } from './dto/get-all-asset-query.dto';
import { GetAllAssetReponseDto } from './dto/get-all-asset-response.dto';
import { Greater } from '@tensorflow/tfjs-core';
@Injectable()
export class AssetService {

2
server/src/config/multer-option.config.ts
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@ -11,7 +11,7 @@ export const multerConfig = {
export const multerOption: MulterOptions = {
fileFilter: (req: Request, file: any, cb: any) => {
if (file.mimetype.match(/\/(jpg|jpeg|png|gif|mp4|x-msvideo|quicktime)$/)) {
if (file.mimetype.match(/\/(jpg|jpeg|png|gif|mp4|x-msvideo|quicktime|heic|heif)$/)) {
cb(null, true);
} else {
cb(new HttpException(`Unsupported file type ${extname(file.originalname)}`, HttpStatus.BAD_REQUEST), false);

11
server/src/modules/image-optimize/image-optimize.module.ts
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@ -7,7 +7,6 @@ import { AssetService } from '../../api-v1/asset/asset.service';
import { AssetEntity } from '../../api-v1/asset/entities/asset.entity';
import { ImageOptimizeProcessor } from './image-optimize.processor';
import { AssetOptimizeService } from './image-optimize.service';
import { MachineLearningProcessor } from './machine-learning.processor';
@Module({
imports: [
@ -19,18 +18,10 @@ import { MachineLearningProcessor } from './machine-learning.processor';
removeOnFail: false,
},
}),
BullModule.registerQueue({
name: 'machine-learning',
defaultJobOptions: {
attempts: 3,
removeOnComplete: true,
removeOnFail: false,
},
}),
TypeOrmModule.forFeature([AssetEntity]),
],
providers: [AssetOptimizeService, ImageOptimizeProcessor, MachineLearningProcessor],
providers: [AssetOptimizeService, ImageOptimizeProcessor],
exports: [AssetOptimizeService],
})
export class ImageOptimizeModule {}

60
server/src/modules/image-optimize/image-optimize.processor.ts
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@ -4,16 +4,16 @@ import { Job, Queue } from 'bull';
import { Repository } from 'typeorm';
import { AssetEntity } from '../../api-v1/asset/entities/asset.entity';
import sharp from 'sharp';
import fs, { existsSync, mkdirSync } from 'fs';
import { existsSync, mkdirSync, readFile } from 'fs';
import { ConfigService } from '@nestjs/config';
import ffmpeg from 'fluent-ffmpeg';
import { Logger } from '@nestjs/common';
@Processor('optimize')
export class ImageOptimizeProcessor {
constructor(
@InjectRepository(AssetEntity) private assetRepository: Repository<AssetEntity>,
@InjectQueue('machine-learning') private machineLearningQueue: Queue,
@InjectRepository(AssetEntity)
private assetRepository: Repository<AssetEntity>,
private configService: ConfigService,
) {}
@ -32,30 +32,42 @@ export class ImageOptimizeProcessor {
mkdirSync(resizeDir, { recursive: true });
}
fs.readFile(savedAsset.originalPath, (err, data) => {
readFile(savedAsset.originalPath, async (err, data) => {
if (err) {
console.error('Error Reading File');
}
sharp(data)
.resize(512, 512, { fit: 'outside' })
.toFile(resizePath, async (err, info) => {
if (err) {
console.error('Error resizing file ', err);
return;
}
await this.assetRepository.update(savedAsset, { resizePath: resizePath });
// Send file to object detection after resizing
// const detectionJob = await this.machineLearningQueue.add(
// 'object-detection',
// {
// resizePath,
// },
// { jobId: randomUUID() },
// );
});
if (savedAsset.mimeType == 'image/heic' || savedAsset.mimeType == 'image/heif') {
let desitnation = '';
if (savedAsset.mimeType == 'image/heic') {
desitnation = resizePath.replace('.HEIC', '.jpeg');
} else {
desitnation = resizePath.replace('.HEIF', '.jpeg');
}
sharp(data)
.toFormat('jpeg')
.resize(512, 512, { fit: 'outside' })
.toFile(desitnation, async (err, info) => {
if (err) {
console.error('Error resizing file ', err);
return;
}
await this.assetRepository.update(savedAsset, { resizePath: desitnation });
});
} else {
sharp(data)
.resize(512, 512, { fit: 'outside' })
.toFile(resizePath, async (err, info) => {
if (err) {
console.error('Error resizing file ', err);
return;
}
await this.assetRepository.update(savedAsset, { resizePath: resizePath });
});
}
});
return 'ok';

38
server/src/modules/image-optimize/machine-learning.processor.ts
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@ -1,38 +0,0 @@
import { Process, Processor } from '@nestjs/bull';
import { InjectRepository } from '@nestjs/typeorm';
import { Job } from 'bull';
import { Repository } from 'typeorm';
import { AssetEntity } from '../../api-v1/asset/entities/asset.entity';
import fs from 'fs';
import { ConfigService } from '@nestjs/config';
import * as tfnode from '@tensorflow/tfjs-node';
import * as cocoSsd from '@tensorflow-models/coco-ssd';
@Processor('machine-learning')
export class MachineLearningProcessor {
constructor(
@InjectRepository(AssetEntity) private assetRepository: Repository<AssetEntity>,
private configService: ConfigService,
) {}
@Process('object-detection')
async handleOptimization(job: Job) {
try {
const { resizePath }: { resizePath: string } = job.data;
const image = fs.readFileSync(resizePath);
const decodedImage = tfnode.node.decodeImage(image, 3) as tfnode.Tensor3D;
const model = await cocoSsd.load();
const predictions = await model.detect(decodedImage);
console.log('\n\nstart predictions ------------------ ');
for (var result of predictions) {
console.log(`Found ${result.class} with score ${result.score}`);
}
console.log('end predictions ------------------\n\n');
return 'ok';
} catch (e) {
console.log('Error object detection ', e);
}
}
}