diff --git a/backend/test_all_regions.py b/backend/test_all_regions.py deleted file mode 100644 index c630ab6..0000000 --- a/backend/test_all_regions.py +++ /dev/null @@ -1,144 +0,0 @@ -#!/usr/bin/env python -""" -測試 calculate_page_dimensions 是否正確檢查所有可能的區域 -包括: text_regions, image_regions, tables, layout, layout_data.elements -""" - -import json -from pathlib import Path -from app.services.pdf_generator_service import pdf_generator_service -import logging - -# Set up logging -logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s') - -def test_all_region_types(): - """ - 測試場景： - - layout: [] (空列表) - - text_regions: 包含文字區域 - - image_regions: 包含圖片區域 (關鍵！) - - tables: 包含表格區域 (關鍵！) - """ - - test_dir = Path("test_output_all_regions") - test_dir.mkdir(exist_ok=True) - - print("\n" + "="*70) - print("測試場景：檢查所有區域類型 (text, image, table)") - print("="*70) - - # 模擬包含所有區域類型的 JSON - mock_ocr_data = { - "status": "success", - "file_name": "complete_document.pdf", - "language": "ch", - "layout": [], # 空列表 - "text_regions": [ - { - "text": "標題文字", - "bbox": [[461, 270], [819, 270], [819, 408], [461, 408]], - "confidence": 0.95 - }, - { - "text": "內容文字", - "bbox": [[1521, 936], [1850, 936], [1850, 1020], [1521, 1020]], - "confidence": 0.93 - } - ], - "image_regions": [ - { - "type": "figure", - "bbox": [[1434, 1500], [2204, 1500], [2204, 2100], [1434, 2100]], # 圖片在右下角 - "image_path": "imgs/figure_1.jpg" - }, - { - "type": "chart", - "bbox": [[200, 2200], [800, 2200], [800, 2800], [200, 2800]], - "image_path": "imgs/chart_1.jpg" - } - ], - "tables": [ - { - "type": "table", - "bbox": [[300, 3000], [1900, 3000], [1900, 3500], [300, 3500]], # 表格在底部 - "html": "...
" - } - ], - "total_text_regions": 2, - "average_confidence": 0.94, - "layout_data": None, - "images_metadata": [], - "markdown_content": "標題文字\n內容文字", - "processing_time": 4.5, - "timestamp": "2025-11-17T00:00:00" - } - - # Save mock JSON - json_path = test_dir / "all_regions_test.json" - with open(json_path, "w", encoding="utf-8") as f: - json.dump(mock_ocr_data, f, ensure_ascii=False, indent=2) - - print(f"\n✓ 創建測試 JSON: {json_path}") - print(f" - layout: [] (空列表)") - print(f" - text_regions: 2 個區域 (max X=1850)") - print(f" - image_regions: 2 個區域 (max X=2204) *** 關鍵！") - print(f" - tables: 1 個區域 (max Y=3500) *** 關鍵！") - print(f" - 預期 OCR 尺寸: ~2204 x ~3500 (取自所有區域的最大值)") - - # Create A4 source PDF - from reportlab.pdfgen import canvas - from reportlab.lib.pagesizes import A4 - - source_pdf = test_dir / "source_a4.pdf" - c = canvas.Canvas(str(source_pdf), pagesize=A4) - c.drawString(100, 800, "Original A4 Document") - c.save() - - print(f"✓ 創建 A4 源文件: {source_pdf}") - print(f" - A4 尺寸: 595 x 842 點") - - # Test PDF generation - pdf_path = test_dir / "output_all_regions.pdf" - - print(f"\n開始生成 PDF...") - print("-" * 70) - - success = pdf_generator_service.generate_layout_pdf( - json_path=json_path, - output_path=pdf_path, - source_file_path=source_pdf - ) - - print("-" * 70) - - if success: - print(f"\n✓ PDF 生成成功: {pdf_path}") - print(f"\n預期結果:") - print(f" - OCR 尺寸（從所有區域推斷）: ~2204 x ~3500") - print(f" - 目標 PDF 尺寸: 595 x 842") - print(f" - 預期縮放因子: X={595/2204:.3f}, Y={842/3500:.3f}") - print(f"\n關鍵驗證:") - print(f" - 如果只檢查 text_regions，max_x 只有 1850 (錯誤！)") - print(f" - 必須檢查 image_regions 才能得到正確的 max_x=2204") - print(f" - 必須檢查 tables 才能得到正確的 max_y=3500") - return True - else: - print(f"\n✗ PDF 生成失敗") - return False - -if __name__ == "__main__": - import sys - sys.path.insert(0, str(Path(__file__).parent)) - - success = test_all_region_types() - - print("\n" + "="*70) - if success: - print("✓ 測試通過！所有區域類型都被正確檢查") - print("="*70) - sys.exit(0) - else: - print("✗ 測試失敗") - print("="*70) - sys.exit(1) \ No newline at end of file diff --git a/backend/test_bbox_scaling.py b/backend/test_bbox_scaling.py deleted file mode 100644 index 5284628..0000000 --- a/backend/test_bbox_scaling.py +++ /dev/null @@ -1,130 +0,0 @@ -#!/usr/bin/env python -""" -Test script for PDF generation with proper bbox-based dimension calculation -Simulates the real scenario where OCR processes on high-res images (e.g., 2189x3500) -but we want to generate PDFs at original size (e.g., A4: 595x842) -""" - -import json -from pathlib import Path -from app.services.pdf_generator_service import pdf_generator_service -import logging - -# Set up logging to see dimension calculations -logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s') - -def test_high_res_ocr_to_a4_pdf(): - """ - Test the scenario user described: - - PaddleOCR processes PDF at high resolution (2189x3500) - - OCR bbox coordinates are in this high-res space - - We want to generate A4 PDF (595x842) - - Scale factors should be ~0.27 and ~0.24 - """ - - # Create test directory - test_dir = Path("test_output_bbox") - test_dir.mkdir(exist_ok=True) - - print("\n" + "="*70) - print("測試場景：高解析度 OCR → A4 PDF 縮放") - print("="*70) - - # Create mock OCR data with high-res bbox coordinates - # Simulating text at various positions in the 2189x3500 coordinate space - mock_ocr_data = { - "status": "success", - "file_name": "test_document.pdf", - "language": "ch", - "text_regions": [ - { - "text": "標題文字在頂部", - "bbox": [[230, 195], [1189, 182], [1189, 350], [230, 363]], # Top of page - "confidence": 0.95 - }, - { - "text": "中間的文字內容", - "bbox": [[1521, 1750], [2185, 1750], [2185, 1820], [1521, 1820]], # Middle - "confidence": 0.92 - }, - { - "text": "底部的文字", - "bbox": [[400, 3200], [1200, 3200], [1200, 3280], [400, 3280]], # Bottom - "confidence": 0.93 - } - ], - "total_text_regions": 3, - "average_confidence": 0.933, - "layout_data": None, - "images_metadata": [], - "markdown_content": "# Test Document\n\n標題文字在頂部\n中間的文字內容\n底部的文字", - "processing_time": 2.5, - "timestamp": "2025-11-17T00:00:00" - } - - # Save mock JSON - json_path = test_dir / "high_res_ocr_result.json" - with open(json_path, "w", encoding="utf-8") as f: - json.dump(mock_ocr_data, f, ensure_ascii=False, indent=2) - - print(f"\n✓ 創建測試 JSON: {json_path}") - print(f" - OCR 座標範圍: X=[230..2185], Y=[182..3280]") - print(f" - 預期 OCR 尺寸: ~2185 x ~3280") - - # Create a mock A4 source PDF for target dimensions - from PIL import Image - from reportlab.lib.pagesizes import A4 - - # Create dummy source image at A4 size (595x842 points) - source_pdf = test_dir / "source_a4.pdf" - - # For this test, we'll create a simple PDF using reportlab - from reportlab.pdfgen import canvas - c = canvas.Canvas(str(source_pdf), pagesize=A4) - c.drawString(100, 800, "Original A4 Document") - c.save() - - print(f"✓ 創建 A4 源文件: {source_pdf}") - print(f" - A4 尺寸: 595 x 842 點") - - # Test PDF generation - pdf_path = test_dir / "scaled_output.pdf" - - print(f"\n開始生成 PDF...") - print("-" * 70) - - success = pdf_generator_service.generate_layout_pdf( - json_path=json_path, - output_path=pdf_path, - source_file_path=source_pdf - ) - - print("-" * 70) - - if success: - print(f"\n✓ PDF 生成成功: {pdf_path}") - print(f"\n預期結果:") - print(f" - OCR 尺寸: ~2185 x ~3280") - print(f" - 目標 PDF 尺寸: 595 x 842") - print(f" - 預期縮放因子: X={595/2185:.3f}, Y={842/3280:.3f}") - print(f"\n實際結果應該與預期一致（見上方日誌）") - return True - else: - print(f"\n✗ PDF 生成失敗") - return False - -if __name__ == "__main__": - import sys - sys.path.insert(0, str(Path(__file__).parent)) - - success = test_high_res_ocr_to_a4_pdf() - - print("\n" + "="*70) - if success: - print("✓ 測試通過！縮放邏輯正確") - print("="*70) - sys.exit(0) - else: - print("✗ 測試失敗") - print("="*70) - sys.exit(1) diff --git a/backend/test_empty_layout.py b/backend/test_empty_layout.py deleted file mode 100644 index cf205fb..0000000 --- a/backend/test_empty_layout.py +++ /dev/null @@ -1,130 +0,0 @@ -#!/usr/bin/env python -""" -測試 calculate_page_dimensions 是否正確處理 layout=[] 但 text_regions 有數據的情況 -這模擬了用戶報告的 ELER-8-100HFV Data Sheet 的場景 -""" - -import json -from pathlib import Path -from app.services.pdf_generator_service import pdf_generator_service -import logging - -# Set up logging -logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s') - -def test_empty_layout_with_text_regions(): - """ - 測試場景： - - layout: [] (空列表) - - text_regions: 包含高解析度 bbox 數據 - - 應該從 text_regions 推斷出正確的 OCR 尺寸 - """ - - test_dir = Path("test_output_empty_layout") - test_dir.mkdir(exist_ok=True) - - print("\n" + "="*70) - print("測試場景：layout=[] 但 text_regions 包含數據") - print("="*70) - - # 模擬用戶的 JSON 結構 - mock_ocr_data = { - "status": "success", - "file_name": "ELER-8-100HFV_Data_Sheet.pdf", - "language": "ch", - "layout": [], # *** 關鍵：這是空的 *** - "text_regions": [ - { - "text": "義典科技", - "bbox": [[461, 270], [819, 252], [822, 408], [464, 426]], # 高解析度座標 - "confidence": 0.95 - }, - { - "text": "ELER-8-100HFV", - "bbox": [[1150, 580], [1850, 580], [1850, 680], [1150, 680]], - "confidence": 0.93 - }, - { - "text": "表格中的文字", - "bbox": [[1259, 936], [1317, 936], [1317, 960], [1259, 960]], # X=1259 超出 A4 寬度 - "confidence": 0.92 - }, - { - "text": "底部文字", - "bbox": [[400, 2800], [1200, 2800], [1200, 2880], [400, 2880]], # Y=2880 - "confidence": 0.91 - } - ], - "total_text_regions": 4, - "average_confidence": 0.928, - "layout_data": None, - "images_metadata": [], - "markdown_content": "義典科技\nELER-8-100HFV\n表格中的文字\n底部文字", - "processing_time": 3.2, - "timestamp": "2025-11-17T00:00:00" - } - - # Save mock JSON - json_path = test_dir / "empty_layout_test.json" - with open(json_path, "w", encoding="utf-8") as f: - json.dump(mock_ocr_data, f, ensure_ascii=False, indent=2) - - print(f"\n✓ 創建測試 JSON: {json_path}") - print(f" - layout: [] (空列表)") - print(f" - text_regions: 4 個區域") - print(f" - OCR 座標範圍: X=[400..1850], Y=[252..2880]") - print(f" - 預期 OCR 尺寸: ~1850 x ~2880") - - # Create A4 source PDF - from reportlab.pdfgen import canvas - from reportlab.lib.pagesizes import A4 - - source_pdf = test_dir / "source_a4.pdf" - c = canvas.Canvas(str(source_pdf), pagesize=A4) - c.drawString(100, 800, "Original A4 Document") - c.save() - - print(f"✓ 創建 A4 源文件: {source_pdf}") - print(f" - A4 尺寸: 595 x 842 點") - - # Test PDF generation - pdf_path = test_dir / "output.pdf" - - print(f"\n開始生成 PDF...") - print("-" * 70) - - success = pdf_generator_service.generate_layout_pdf( - json_path=json_path, - output_path=pdf_path, - source_file_path=source_pdf - ) - - print("-" * 70) - - if success: - print(f"\n✓ PDF 生成成功: {pdf_path}") - print(f"\n預期結果:") - print(f" - OCR 尺寸（從 text_regions 推斷）: ~1850 x ~2880") - print(f" - 目標 PDF 尺寸: 595 x 842") - print(f" - 預期縮放因子: X={595/1850:.3f}, Y={842/2880:.3f}") - print(f"\n如果實際縮放因子是 1.0，說明 Bug 仍存在！") - return True - else: - print(f"\n✗ PDF 生成失敗") - return False - -if __name__ == "__main__": - import sys - sys.path.insert(0, str(Path(__file__).parent)) - - success = test_empty_layout_with_text_regions() - - print("\n" + "="*70) - if success: - print("✓ 測試完成") - print("="*70) - sys.exit(0) - else: - print("✗ 測試失敗") - print("="*70) - sys.exit(1) diff --git a/backend/test_pdf_scaling.py b/backend/test_pdf_scaling.py deleted file mode 100644 index 7424097..0000000 --- a/backend/test_pdf_scaling.py +++ /dev/null @@ -1,100 +0,0 @@ -#!/usr/bin/env python -""" -Test script for PDF generation with proper scaling -""" - -import json -from pathlib import Path -from app.services.pdf_generator_service import pdf_generator_service - -def test_pdf_generation(): - """Test PDF generation with mock data that includes OCR dimensions""" - - # Create a test directory - test_dir = Path("test_output") - test_dir.mkdir(exist_ok=True) - - # Create mock OCR JSON data with OCR dimensions - mock_ocr_data = { - "status": "success", - "file_name": "test_image.jpg", - "language": "ch", - "ocr_dimensions": { - "width": 500, # OCR processed at 500px wide - "height": 700 # OCR processed at 700px tall - }, - "text_regions": [ - { - "text": "測試文字 Test Text", - "bbox": [[50, 100], [250, 100], [250, 150], [50, 150]], - "confidence": 0.95 - }, - { - "text": "第二行文字 Second line", - "bbox": [[50, 200], [300, 200], [300, 250], [50, 250]], - "confidence": 0.92 - } - ], - "total_text_regions": 2, - "average_confidence": 0.935, - "layout_data": None, - "images_metadata": [], - "markdown_content": "# Test Document\n\n測試文字 Test Text\n\n第二行文字 Second line", - "processing_time": 1.5, - "timestamp": "2025-11-17T00:00:00" - } - - # Save mock JSON - json_path = test_dir / "test_ocr_result.json" - with open(json_path, "w", encoding="utf-8") as f: - json.dump(mock_ocr_data, f, ensure_ascii=False, indent=2) - - print(f"Created test JSON at: {json_path}") - - # Test PDF generation - pdf_path = test_dir / "test_output.pdf" - - # Create a dummy source file for dimensions (1000x1400 target PDF size) - from PIL import Image - source_image = test_dir / "test_source.jpg" - img = Image.new('RGB', (1000, 1400), color='white') - img.save(source_image) - print(f"Created test source image: {source_image} (1000x1400)") - - # Generate PDF - print("\nGenerating PDF with scaling...") - - # Set up logging to see scale factors - import logging - logging.basicConfig(level=logging.INFO, format='%(message)s') - - success = pdf_generator_service.generate_layout_pdf( - json_path=json_path, - output_path=pdf_path, - source_file_path=source_image - ) - - if success: - print(f"✓ PDF generated successfully: {pdf_path}") - print(f" Expected scale factors: X={1000/500:.2f}, Y={1400/700:.2f}") - print(" Text should now be properly scaled and positioned!") - else: - print("✗ PDF generation failed") - - return success - -if __name__ == "__main__": - import sys - sys.path.insert(0, str(Path(__file__).parent)) - - print("Testing PDF generation with proper scaling...") - print("=" * 60) - - success = test_pdf_generation() - - print("\n" + "=" * 60) - if success: - print("✓ Test completed successfully!") - print("Check test_output/test_output.pdf to verify scaling") - else: - print("✗ Test failed") \ No newline at end of file