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immich/server/src/domain/smart-info/smart-info.service.ts

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import { Inject, Injectable, Logger } from '@nestjs/common';
import { IAssetRepository, WithoutProperty } from '../asset';
2023-03-24 00:55:15 -04:00
import { MACHINE_LEARNING_ENABLED } from '../domain.constant';
import { usePagination } from '../domain.util';
import { IBaseJob, IEntityJob, IJobRepository, JobName, JOBS_ASSET_PAGINATION_SIZE } from '../job';
import { IMachineLearningRepository } from './machine-learning.interface';
import { ISmartInfoRepository } from './smart-info.repository';
@Injectable()
export class SmartInfoService {
private logger = new Logger(SmartInfoService.name);
constructor(
@Inject(IAssetRepository) private assetRepository: IAssetRepository,
@Inject(IJobRepository) private jobRepository: IJobRepository,
@Inject(ISmartInfoRepository) private repository: ISmartInfoRepository,
@Inject(IMachineLearningRepository) private machineLearning: IMachineLearningRepository,
) {}
async handleQueueObjectTagging({ force }: IBaseJob) {
const assetPagination = usePagination(JOBS_ASSET_PAGINATION_SIZE, (pagination) => {
return force
? this.assetRepository.getAll(pagination)
: this.assetRepository.getWithout(pagination, WithoutProperty.OBJECT_TAGS);
});
for await (const assets of assetPagination) {
for (const asset of assets) {
await this.jobRepository.queue({ name: JobName.CLASSIFY_IMAGE, data: { id: asset.id } });
}
}
return true;
}
async handleClassifyImage({ id }: IEntityJob) {
const [asset] = await this.assetRepository.getByIds([id]);
if (!MACHINE_LEARNING_ENABLED || !asset.resizePath) {
return false;
}
const tags = await this.machineLearning.classifyImage({ imagePath: asset.resizePath });
await this.repository.upsert({ assetId: asset.id, tags });
return true;
}
async handleQueueEncodeClip({ force }: IBaseJob) {
const assetPagination = usePagination(JOBS_ASSET_PAGINATION_SIZE, (pagination) => {
return force
? this.assetRepository.getAll(pagination)
: this.assetRepository.getWithout(pagination, WithoutProperty.CLIP_ENCODING);
});
for await (const assets of assetPagination) {
for (const asset of assets) {
await this.jobRepository.queue({ name: JobName.ENCODE_CLIP, data: { id: asset.id } });
}
}
return true;
}
async handleEncodeClip({ id }: IEntityJob) {
const [asset] = await this.assetRepository.getByIds([id]);
if (!MACHINE_LEARNING_ENABLED || !asset.resizePath) {
return false;
}
const clipEmbedding = await this.machineLearning.encodeImage({ imagePath: asset.resizePath });
await this.repository.upsert({ assetId: asset.id, clipEmbedding: clipEmbedding });
return true;
}
}