Added three key documentation files: 1. TEST_ACCURACY_BATCH_README.md - Complete usage guide for test_accuracy_batch_full.py - Command-line parameters reference - 4 usage scenarios (quick, high-accuracy, fast, single-PDF) - Troubleshooting guide - Performance optimization tips - Best practices and examples 2. TEST_ACCURACY_BATCH_DEPENDENCIES.md - Detailed dependency analysis - Required files and directory structure - Python library dependencies - File size statistics - Dependency relationship diagram - Common dependency issues and solutions 3. CLEANUP_PLAN.md - File categorization (keep, archive, delete) - Step-by-step cleanup instructions - Archive directory structure proposal - Three cleanup approaches (conservative, aggressive, phased) - Cleanup automation script Features: - Comprehensive parameter reference tables - Real-world usage examples - Performance comparison charts - Quick reference commands - Development guidelines Target audience: - New developers joining the project - QA team running batch tests - DevOps engineers deploying the system Related: - test_accuracy_batch_full.py (v1.2.0) - PADDLEOCRVL_TIMEOUT_FIX_SUMMARY.md - IMPLEMENTATION_SUMMARY.md Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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|---|---|---|
| data | ||
| report_viz | ||
| scripts | ||
| src | ||
| temp_classpath | ||
| .gitignore | ||
| BUILD_REPORT.md | ||
| CLEANUP_PLAN.md | ||
| COMPREHENSIVE_REPORT.md | ||
| DJL_UPGRADE_ATTEMPT_REPORT.md | ||
| IMPLEMENTATION_SUMMARY.md | ||
| INTEGRATION_GUIDE.md | ||
| INTEGRATION_TEST_REPORT.md | ||
| ManualTest.java | ||
| PADDLEOCRVL_INTEGRATION.md | ||
| README.md | ||
| TEST_ACCURACY_BATCH_DEPENDENCIES.md | ||
| TEST_ACCURACY_BATCH_README.md | ||
| cma_extraction_template_primary.py | ||
| jar_paths.txt | ||
| pom.xml | ||
| reply.md | ||
| res.json | ||
| run_reference_test.bat | ||
| run_test.bat | ||
| run_test_v2.bat | ||
| run_viz_report.bat | ||
| settings.xml | ||
| test_accuracy_batch_full.py | ||
| test_paddleocr_vl_quick.py | ||
| v_verify_logic.py | ||
| 测试结果汇总.txt | ||
README.md
Report Detection Backend
Java-based backend system for automated report validation and comparison using OCR.
Technology Stack
- Core: Java 8 (Spring Boot 2.7.18)
- Security: Sa-Token (RBAC, Session Management)
- OCR Engine: PaddleOCR (via DJL - Deep Java Library)
- Database: PostgreSQL (with Dynamic Datasource support)
- Build Tool: Maven
Features
- RBAC Implementation: Multi-role support (ADMIN, AUDITOR, USER) with uppercase standardization.
- Sa-Token Security: Annotation-based permission checks and secure login.
- Auditor Context Switch: Specialized feature for Auditors to switch between institutional views.
- PDF Processing: Automatic conversion of PDF reports to images for OCR analysis.
- Automated Verification: Integration tests using H2 in-memory database.
Getting Started
Prerequisites
- JDK 8 or 17
- Maven 3.6+
- PostgreSQL (optional for local dev if using H2 profile)
Run the Application
mvn clean package
java -jar target/report-detect-backend-1.0.0.jar
Run Tests
mvn test -Dtest=SecurityRBACVerificationTest
Security Configuration
Default accounts created on initialization:
admin/123456(ADMIN)auditor/123456(AUDITOR)user/123456(USER)