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

108 lines
3.5 KiB
TypeScript

import { Inject, Injectable } from '@nestjs/common';
import { IAssetRepository, WithoutProperty } from '../asset';
import { usePagination } from '../domain.util';
import { IBaseJob, IEntityJob, IJobRepository, JOBS_ASSET_PAGINATION_SIZE, JobName } from '../job';
import { ISystemConfigRepository, SystemConfigCore } from '../system-config';
import { IMachineLearningRepository } from './machine-learning.interface';
import { ISmartInfoRepository } from './smart-info.repository';
@Injectable()
export class SmartInfoService {
private configCore: SystemConfigCore;
constructor(
@Inject(IAssetRepository) private assetRepository: IAssetRepository,
@Inject(ISystemConfigRepository) configRepository: ISystemConfigRepository,
@Inject(IJobRepository) private jobRepository: IJobRepository,
@Inject(ISmartInfoRepository) private repository: ISmartInfoRepository,
@Inject(IMachineLearningRepository) private machineLearning: IMachineLearningRepository,
) {
this.configCore = new SystemConfigCore(configRepository);
}
async handleQueueObjectTagging({ force }: IBaseJob) {
const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.classification.enabled) {
return true;
}
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 { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.classification.enabled) {
return true;
}
const [asset] = await this.assetRepository.getByIds([id]);
if (!asset.resizePath) {
return false;
}
const tags = await this.machineLearning.classifyImage(
machineLearning.url,
{ imagePath: asset.resizePath },
machineLearning.classification,
);
await this.repository.upsert({ assetId: asset.id, tags });
return true;
}
async handleQueueEncodeClip({ force }: IBaseJob) {
const { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.clip.enabled) {
return true;
}
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 { machineLearning } = await this.configCore.getConfig();
if (!machineLearning.enabled || !machineLearning.clip.enabled) {
return true;
}
const [asset] = await this.assetRepository.getByIds([id]);
if (!asset.resizePath) {
return false;
}
const clipEmbedding = await this.machineLearning.encodeImage(
machineLearning.url,
{ imagePath: asset.resizePath },
machineLearning.clip,
);
await this.repository.upsert({ assetId: asset.id, clipEmbedding: clipEmbedding });
return true;
}
}