mirror of
https://github.com/immich-app/immich.git
synced 2026-05-18 03:10:24 +03:00
fix(server): use bigrams for cjk (#24285)
* use bigrams for cjk * update sql * linting * actually migrate ocr * fix backwards test * use array * tweaks
This commit is contained in:
@@ -12,8 +12,21 @@ describe(OcrService.name, () => {
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({ sut, mocks } = newTestService(OcrService));
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mocks.config.getWorker.mockReturnValue(ImmichWorker.Microservices);
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mocks.assetJob.getForOcr.mockResolvedValue({
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visibility: AssetVisibility.Timeline,
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previewFile: assetStub.image.files[1].path,
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});
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});
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const mockOcrResult = (...texts: string[]) => {
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mocks.machineLearning.ocr.mockResolvedValue({
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box: texts.flatMap((_, i) => Array.from({ length: 8 }, (_, j) => i * 10 + j)),
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boxScore: texts.map(() => 0.9),
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text: texts,
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textScore: texts.map(() => 0.95),
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});
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};
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it('should work', () => {
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expect(sut).toBeDefined();
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});
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@@ -72,10 +85,6 @@ describe(OcrService.name, () => {
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text: ['One Two Three', 'Four Five'],
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textScore: [0.95, 0.85],
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});
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mocks.assetJob.getForOcr.mockResolvedValue({
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visibility: AssetVisibility.Timeline,
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previewFile: assetStub.image.files[1].path,
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});
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expect(await sut.handleOcr({ id: assetStub.image.id })).toEqual(JobStatus.Success);
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@@ -88,36 +97,40 @@ describe(OcrService.name, () => {
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maxResolution: 736,
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}),
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);
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, [
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{
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assetId: assetStub.image.id,
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boxScore: 0.9,
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text: 'One Two Three',
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textScore: 0.95,
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x1: 10,
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y1: 20,
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x2: 30,
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y2: 40,
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x3: 50,
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y3: 60,
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x4: 70,
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y4: 80,
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},
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{
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assetId: assetStub.image.id,
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boxScore: 0.8,
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text: 'Four Five',
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textScore: 0.85,
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x1: 90,
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y1: 100,
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x2: 110,
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y2: 120,
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x3: 130,
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y3: 140,
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x4: 150,
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y4: 160,
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},
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]);
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(
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assetStub.image.id,
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[
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{
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assetId: assetStub.image.id,
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boxScore: 0.9,
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text: 'One Two Three',
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textScore: 0.95,
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x1: 10,
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y1: 20,
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x2: 30,
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y2: 40,
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x3: 50,
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y3: 60,
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x4: 70,
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y4: 80,
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},
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{
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assetId: assetStub.image.id,
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boxScore: 0.8,
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text: 'Four Five',
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textScore: 0.85,
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x1: 90,
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y1: 100,
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x2: 110,
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y2: 120,
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x3: 130,
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y3: 140,
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x4: 150,
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y4: 160,
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},
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],
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'One Two Three Four Five',
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);
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});
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it('should apply config settings', async () => {
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@@ -133,11 +146,7 @@ describe(OcrService.name, () => {
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},
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},
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});
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mocks.machineLearning.ocr.mockResolvedValue({ box: [], boxScore: [], text: [], textScore: [] });
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mocks.assetJob.getForOcr.mockResolvedValue({
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visibility: AssetVisibility.Timeline,
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previewFile: assetStub.image.files[1].path,
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});
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mockOcrResult();
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expect(await sut.handleOcr({ id: assetStub.image.id })).toEqual(JobStatus.Success);
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@@ -150,7 +159,7 @@ describe(OcrService.name, () => {
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maxResolution: 1500,
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}),
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);
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, []);
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, [], '');
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});
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it('should skip invisible assets', async () => {
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@@ -173,5 +182,83 @@ describe(OcrService.name, () => {
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expect(mocks.machineLearning.ocr).not.toHaveBeenCalled();
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expect(mocks.ocr.upsert).not.toHaveBeenCalled();
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});
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describe('search tokenization', () => {
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it('should generate bigrams for Chinese text', async () => {
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mockOcrResult('機器學習');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), '機器 器學 學習');
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});
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it('should generate bigrams for Japanese text', async () => {
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mockOcrResult('テスト');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), 'テス スト');
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});
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it('should generate bigrams for Korean text', async () => {
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mockOcrResult('한국어');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), '한국 국어');
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});
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it('should pass through Latin text unchanged', async () => {
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mockOcrResult('Hello World');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), 'Hello World');
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});
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it('should handle mixed CJK and Latin text', async () => {
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mockOcrResult('機器學習Model');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), '機器 器學 學習 Model');
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});
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it('should handle year followed by CJK', async () => {
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mockOcrResult('2024年レポート');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(
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assetStub.image.id,
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expect.any(Array),
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'2024 年レ レポ ポー ート',
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);
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});
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it('should join multiple OCR boxes', async () => {
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mockOcrResult('機器', 'Learning');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), '機器 Learning');
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});
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it('should normalize whitespace', async () => {
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mockOcrResult(' Hello World ');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), 'Hello World');
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});
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it('should keep single CJK characters', async () => {
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mockOcrResult('A', '中', 'B');
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await sut.handleOcr({ id: assetStub.image.id });
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expect(mocks.ocr.upsert).toHaveBeenCalledWith(assetStub.image.id, expect.any(Array), 'A 中 B');
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});
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});
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});
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});
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@@ -5,6 +5,7 @@ import { AssetVisibility, JobName, JobStatus, QueueName } from 'src/enum';
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import { OCR } from 'src/repositories/machine-learning.repository';
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import { BaseService } from 'src/services/base.service';
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import { JobItem, JobOf } from 'src/types';
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import { tokenizeForSearch } from 'src/utils/database';
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import { isOcrEnabled } from 'src/utils/misc';
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@Injectable()
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@@ -53,8 +54,8 @@ export class OcrService extends BaseService {
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}
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const ocrResults = await this.machineLearningRepository.ocr(asset.previewFile, machineLearning.ocr);
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await this.ocrRepository.upsert(id, this.parseOcrResults(id, ocrResults));
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const { ocrDataList, searchText } = this.parseOcrResults(id, ocrResults);
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await this.ocrRepository.upsert(id, ocrDataList, searchText);
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await this.assetRepository.upsertJobStatus({ assetId: id, ocrAt: new Date() });
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@@ -64,7 +65,9 @@ export class OcrService extends BaseService {
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private parseOcrResults(id: string, { box, boxScore, text, textScore }: OCR) {
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const ocrDataList = [];
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const searchTokens = [];
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for (let i = 0; i < text.length; i++) {
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const rawText = text[i];
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const boxOffset = i * 8;
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ocrDataList.push({
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assetId: id,
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@@ -78,9 +81,11 @@ export class OcrService extends BaseService {
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y4: box[boxOffset + 7],
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boxScore: boxScore[i],
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textScore: textScore[i],
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text: text[i],
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text: rawText,
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});
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searchTokens.push(...tokenizeForSearch(rawText));
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}
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return ocrDataList;
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return { ocrDataList, searchText: searchTokens.join(' ') };
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}
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}
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