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| import pytest | |
| from PIL import Image, ImageDraw, ImageFont | |
| import numpy as np | |
| class TestOCRFunctionality: | |
| """Test OCR text extraction functionality""" | |
| def test_preprocess_image_for_ocr(self, sample_image): | |
| """Test image preprocessing for OCR""" | |
| # Mock the preprocessing function | |
| def mock_preprocess_image_for_ocr(image): | |
| img_array = np.array(image) | |
| if len(img_array.shape) == 3: | |
| gray = np.mean(img_array, axis=2).astype(np.uint8) | |
| else: | |
| gray = img_array | |
| return gray | |
| result = mock_preprocess_image_for_ocr(sample_image) | |
| assert isinstance(result, np.ndarray) | |
| assert len(result.shape) == 2 # Should be grayscale | |
| def test_extract_text_from_image_none_input(self): | |
| """Test OCR with None input""" | |
| def mock_extract_text_from_image(image): | |
| if image is None: | |
| return "❌ No image provided" | |
| return "Sample extracted text" | |
| result = mock_extract_text_from_image(None) | |
| assert result == "❌ No image provided" | |
| def test_extract_text_from_valid_image(self, sample_image): | |
| """Test OCR with valid image""" | |
| def mock_extract_text_from_image(image): | |
| if image is None: | |
| return "❌ No image provided" | |
| # Simulate successful OCR | |
| return "Patient: John Doe, 35-year-old male with chest pain" | |
| result = mock_extract_text_from_image(sample_image) | |
| assert "Patient:" in result | |
| assert "chest pain" in result | |
| def test_clean_extracted_text(self): | |
| """Test text cleaning functionality""" | |
| def mock_clean_extracted_text(text): | |
| lines = [line.strip() for line in text.split('\n') if line.strip()] | |
| cleaned_text = '\n'.join(lines) | |
| cleaned_text = cleaned_text.replace('|', '').replace('_', ' ') | |
| return cleaned_text.strip() | |
| dirty_text = " Line 1 \n\n Line 2 with | pipes \n \n Line_3 " | |
| clean_text = mock_clean_extracted_text(dirty_text) | |
| assert "Line 1" in clean_text | |
| assert "Line 2 with pipes" in clean_text | |
| assert "Line 3" in clean_text | |
| assert "|" not in clean_text | |
| def test_image_preprocessing_edge_cases(self): | |
| """Test image preprocessing with edge cases""" | |
| def mock_preprocess_image_for_ocr(image): | |
| if image is None: | |
| return None | |
| img_array = np.array(image) | |
| # Handle grayscale images | |
| if len(img_array.shape) == 2: | |
| return img_array | |
| # Handle RGB images | |
| elif len(img_array.shape) == 3: | |
| return np.mean(img_array, axis=2).astype(np.uint8) | |
| else: | |
| raise ValueError("Unsupported image format") | |
| # Test with None | |
| assert mock_preprocess_image_for_ocr(None) is None | |
| # Test with small grayscale image | |
| small_gray = Image.new('L', (50, 50), color=128) | |
| result = mock_preprocess_image_for_ocr(small_gray) | |
| assert isinstance(result, np.ndarray) | |
| assert len(result.shape) == 2 |