99 lines
3.4 KiB
TypeScript
99 lines
3.4 KiB
TypeScript
import { Inject, Injectable } from '@nestjs/common';
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import { IAssetRepository, WithoutProperty } from '../asset';
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import { usePagination } from '../domain.util';
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import { IBaseJob, IEntityJob, IJobRepository, JobName, JOBS_ASSET_PAGINATION_SIZE } from '../job';
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import { ISystemConfigRepository, SystemConfigCore } from '../system-config';
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import { IMachineLearningRepository } from './machine-learning.interface';
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import { ISmartInfoRepository } from './smart-info.repository';
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@Injectable()
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export class SmartInfoService {
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private configCore: SystemConfigCore;
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constructor(
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@Inject(IAssetRepository) private assetRepository: IAssetRepository,
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@Inject(ISystemConfigRepository) configRepository: ISystemConfigRepository,
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@Inject(IJobRepository) private jobRepository: IJobRepository,
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@Inject(ISmartInfoRepository) private repository: ISmartInfoRepository,
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@Inject(IMachineLearningRepository) private machineLearning: IMachineLearningRepository,
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) {
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this.configCore = new SystemConfigCore(configRepository);
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}
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async handleQueueObjectTagging({ force }: IBaseJob) {
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const { machineLearning } = await this.configCore.getConfig();
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if (!machineLearning.enabled || !machineLearning.tagImageEnabled) {
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return true;
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}
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const assetPagination = usePagination(JOBS_ASSET_PAGINATION_SIZE, (pagination) => {
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return force
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? this.assetRepository.getAll(pagination)
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: this.assetRepository.getWithout(pagination, WithoutProperty.OBJECT_TAGS);
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});
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for await (const assets of assetPagination) {
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for (const asset of assets) {
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await this.jobRepository.queue({ name: JobName.CLASSIFY_IMAGE, data: { id: asset.id } });
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}
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}
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return true;
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}
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async handleClassifyImage({ id }: IEntityJob) {
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const { machineLearning } = await this.configCore.getConfig();
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if (!machineLearning.enabled || !machineLearning.tagImageEnabled) {
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return true;
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}
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const [asset] = await this.assetRepository.getByIds([id]);
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if (!asset.resizePath) {
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return false;
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}
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const tags = await this.machineLearning.classifyImage(machineLearning.url, { imagePath: asset.resizePath });
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await this.repository.upsert({ assetId: asset.id, tags });
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return true;
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}
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async handleQueueEncodeClip({ force }: IBaseJob) {
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const { machineLearning } = await this.configCore.getConfig();
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if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) {
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return true;
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}
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const assetPagination = usePagination(JOBS_ASSET_PAGINATION_SIZE, (pagination) => {
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return force
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? this.assetRepository.getAll(pagination)
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: this.assetRepository.getWithout(pagination, WithoutProperty.CLIP_ENCODING);
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});
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for await (const assets of assetPagination) {
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for (const asset of assets) {
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await this.jobRepository.queue({ name: JobName.ENCODE_CLIP, data: { id: asset.id } });
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}
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}
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return true;
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}
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async handleEncodeClip({ id }: IEntityJob) {
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const { machineLearning } = await this.configCore.getConfig();
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if (!machineLearning.enabled || !machineLearning.clipEncodeEnabled) {
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return true;
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}
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const [asset] = await this.assetRepository.getByIds([id]);
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if (!asset.resizePath) {
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return false;
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}
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const clipEmbedding = await this.machineLearning.encodeImage(machineLearning.url, { imagePath: asset.resizePath });
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await this.repository.upsert({ assetId: asset.id, clipEmbedding: clipEmbedding });
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return true;
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}
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}
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