feat: ocr (#18836)

* feat: add OCR functionality and related configurations * chore: update labeler configuration for machine learning files * feat(i18n): enhance OCR model descriptions and add orientation classification and unwarping features * chore: update Dockerfile to include ccache for improved build performance * feat(ocr): enhance OCR model configuration with orientation classification and unwarping options, update PaddleOCR integration, and improve response structure * refactor(ocr): remove OCR_CLEANUP job from enum and type definitions * refactor(ocr): remove obsolete OCR entity and migration files, and update asset job status and schema to accommodate new OCR table structure * refactor(ocr): update OCR schema and response structure to use individual coordinates instead of bounding box, and adjust related service and repository files * feat: enhance OCR configuration and functionality - Updated OCR settings to include minimum detection box score, minimum detection score, and minimum recognition score. - Refactored PaddleOCRecognizer to utilize new scoring parameters. - Introduced new database tables for asset OCR data and search functionality. - Modified related services and repositories to support the new OCR features. - Updated translations for improved clarity in settings UI. * sql changes * use rapidocr * change dto * update web * update lock * update api * store positions as normalized floats * match column order in db * update admin ui settings descriptions fix max resolution key set min threshold to 0.1 fix bind * apply config correctly, adjust defaults * unnecessary model type * unnecessary sources * fix(ocr): switch RapidOCR lang type from LangDet to LangRec * fix(ocr): expose lang_type (LangRec.CH) and font_path on OcrOptions for RapidOCR * fix(ocr): make OCR text search case- and accent-insensitive using ILIKE + unaccent * fix(ocr): add OCR search fields * fix: Add OCR database migration and update ML prediction logic. * trigrams are already case insensitive * add tests * format * update migrations * wrong uuid function * linting * maybe fix medium tests * formatting * fix weblate check * openapi * sql * minor fixes * maybe fix medium tests part 2 * passing medium tests * format web * readd sql * format dart * disabled in e2e * chore: translation ordering --------- Co-authored-by: mertalev <101130780+mertalev@users.noreply.github.com> Co-authored-by: Alex Tran <alex.tran1502@gmail.com>
2026-05-18 03:10:24 +03:00 · 2025-10-27 22:09:55 +08:00
parent c666dc6c67
commit 02b29046b3
90 changed files with 3610 additions and 1722 deletions
@@ -0,0 +1,86 @@
+import { Injectable } from '@nestjs/common';
+import { JOBS_ASSET_PAGINATION_SIZE } from 'src/constants';
+import { OnJob } from 'src/decorators';
+import { AssetVisibility, JobName, JobStatus, QueueName } from 'src/enum';
+import { OCR } from 'src/repositories/machine-learning.repository';
+import { BaseService } from 'src/services/base.service';
+import { JobItem, JobOf } from 'src/types';
+import { isOcrEnabled } from 'src/utils/misc';
+
+@Injectable()
+export class OcrService extends BaseService {
+  @OnJob({ name: JobName.OcrQueueAll, queue: QueueName.Ocr })
+  async handleQueueOcr({ force }: JobOf<JobName.OcrQueueAll>): Promise<JobStatus> {
+    const { machineLearning } = await this.getConfig({ withCache: false });
+    if (!isOcrEnabled(machineLearning)) {
+      return JobStatus.Skipped;
+    }
+
+    if (force) {
+      await this.ocrRepository.deleteAll();
+    }
+
+    let jobs: JobItem[] = [];
+    const assets = this.assetJobRepository.streamForOcrJob(force);
+
+    for await (const asset of assets) {
+      jobs.push({ name: JobName.Ocr, data: { id: asset.id } });
+
+      if (jobs.length >= JOBS_ASSET_PAGINATION_SIZE) {
+        await this.jobRepository.queueAll(jobs);
+        jobs = [];
+      }
+    }
+
+    await this.jobRepository.queueAll(jobs);
+    return JobStatus.Success;
+  }
+
+  @OnJob({ name: JobName.Ocr, queue: QueueName.Ocr })
+  async handleOcr({ id }: JobOf<JobName.Ocr>): Promise<JobStatus> {
+    const { machineLearning } = await this.getConfig({ withCache: true });
+    if (!isOcrEnabled(machineLearning)) {
+      return JobStatus.Skipped;
+    }
+
+    const asset = await this.assetJobRepository.getForOcr(id);
+    if (!asset || !asset.previewFile) {
+      return JobStatus.Failed;
+    }
+
+    if (asset.visibility === AssetVisibility.Hidden) {
+      return JobStatus.Skipped;
+    }
+
+    const ocrResults = await this.machineLearningRepository.ocr(asset.previewFile, machineLearning.ocr);
+
+    await this.ocrRepository.upsert(id, this.parseOcrResults(id, ocrResults));
+
+    await this.assetRepository.upsertJobStatus({ assetId: id, ocrAt: new Date() });
+
+    this.logger.debug(`Processed ${ocrResults.text.length} OCR result(s) for ${id}`);
+    return JobStatus.Success;
+  }
+
+  private parseOcrResults(id: string, { box, boxScore, text, textScore }: OCR) {
+    const ocrDataList = [];
+    for (let i = 0; i < text.length; i++) {
+      const boxOffset = i * 8;
+      ocrDataList.push({
+        assetId: id,
+        x1: box[boxOffset],
+        y1: box[boxOffset + 1],
+        x2: box[boxOffset + 2],
+        y2: box[boxOffset + 3],
+        x3: box[boxOffset + 4],
+        y3: box[boxOffset + 5],
+        x4: box[boxOffset + 6],
+        y4: box[boxOffset + 7],
+        boxScore: boxScore[i],
+        textScore: textScore[i],
+        text: text[i],
+      });
+    }
+    return ocrDataList;
+  }
+}