image cleaner

scripts/ex/demo.py

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+#!/usr/bin/env python3
+"""
+Demo Script for Newspaper Image Cleaning Pipeline
+
+This script demonstrates the cleaning pipeline on the sample images
+and shows the available functionality.
+"""
+
+import sys
+import os
+from pathlib import Path
+
+# Add current directory to Python path
+sys.path.append(str(Path(__file__).parent))
+
+try:
+    from image_cleaner import NewspaperImageCleaner, create_comparison_image
+    import cv2
+    import numpy as np
+    print("✓ All required libraries imported successfully")
+except ImportError as e:
+    print(f"✗ Import error: {e}")
+    print("Please install required packages: pip install -r requirements.txt")
+    sys.exit(1)
+
+
+def demo_single_image(image_path):
+    """Demonstrate processing a single image."""
+    print(f"\n=== Processing Single Image: {image_path} ===")
+
+    if not os.path.exists(image_path):
+        print(f"Image not found: {image_path}")
+        return False
+
+    try:
+        # Initialize cleaner
+        cleaner = NewspaperImageCleaner()
+
+        # Process image
+        output_path = f"demo_cleaned_{Path(image_path).name}"
+        processed, original = cleaner.process_image(image_path, output_path)
+
+        # Create comparison
+        comparison_path = f"demo_comparison_{Path(image_path).name}"
+        create_comparison_image(original, processed, comparison_path)
+
+        print(f"✓ Processed image saved: {output_path}")
+        print(f"✓ Comparison saved: {comparison_path}")
+        return True
+
+    except Exception as e:
+        print(f"✗ Error processing {image_path}: {str(e)}")
+        return False
+
+
+def demo_step_by_step(image_path):
+    """Demonstrate individual processing steps."""
+    print(f"\n=== Step-by-Step Processing: {image_path} ===")
+
+    if not os.path.exists(image_path):
+        print(f"Image not found: {image_path}")
+        return
+
+    try:
+        # Load image
+        original = cv2.imread(image_path)
+        if original is None:
+            print(f"Could not load image: {image_path}")
+            return
+
+        # Resize if too large for demo
+        height, width = original.shape[:2]
+        if height > 1000 or width > 1000:
+            scale = min(1000/height, 1000/width)
+            new_width = int(width * scale)
+            new_height = int(height * scale)
+            original = cv2.resize(original, (new_width, new_height))
+            print(f"Resized to {new_width}x{new_height} for demo")
+
+        cleaner = NewspaperImageCleaner()
+
+        # Process step by step
+        steps = [
+            ('original', original),
+            ('denoised', cleaner.reduce_noise(original.copy())),
+            ('contrast_enhanced', cleaner.enhance_contrast(original.copy())),
+            ('background_cleaned', cleaner.clean_background(original.copy())),
+            ('sharpened', cleaner.sharpen_image(original.copy()))
+        ]
+
+        # Save each step
+        for step_name, image in steps:
+            output_path = f"demo_step_{step_name}_{Path(image_path).name}"
+            cv2.imwrite(output_path, image)
+            print(f"✓ Saved {step_name}: {output_path}")
+
+        print("✓ Individual processing steps completed")
+
+    except Exception as e:
+        print(f"✗ Error in step-by-step processing: {str(e)}")
+
+
+def show_image_info():
+    """Show information about available images."""
+    print("\n=== Available Sample Images ===")
+
+    image_files = []
+    for ext in ['*.jpg', '*.jpeg', '*.JPG', '*.JPEG']:
+        image_files.extend(Path('.').glob(ext))
+
+    if not image_files:
+        print("No image files found in current directory")
+        return []
+
+    for img_file in image_files:
+        try:
+            # Load image to get dimensions
+            img = cv2.imread(str(img_file))
+            if img is not None:
+                height, width = img.shape[:2]
+                file_size = img_file.stat().st_size / (1024*1024)  # MB
+                print(f"  {img_file.name}: {width}x{height} pixels, {file_size:.1f}MB")
+            else:
+                print(f"  {img_file.name}: Could not load")
+        except Exception as e:
+            print(f"  {img_file.name}: Error - {str(e)}")
+
+    return image_files
+
+
+def main():
+    """Main demo function."""
+    print("Historical Newspaper Image Cleaning Pipeline - Demo")
+    print("=" * 55)
+
+    # Show available images
+    image_files = show_image_info()
+
+    if not image_files:
+        print("\nNo images found. Please add some image files to test.")
+        return
+
+    # Select first image for demo
+    sample_image = image_files[0]
+    print(f"\nUsing sample image: {sample_image.name}")
+
+    # Demo single image processing
+    success = demo_single_image(str(sample_image))
+
+    if success:
+        # Demo step-by-step processing
+        demo_step_by_step(str(sample_image))
+
+        print(f"\n=== Demo Complete ===")
+        print("Generated files:")
+        print("  - demo_cleaned_*.jpg (cleaned image)")
+        print("  - demo_comparison_*.jpg (before/after comparison)")
+        print("  - demo_step_*.jpg (individual processing steps)")
+
+        print(f"\nNext steps:")
+        print(f"  - Try: python config_tuner.py {sample_image.name}")
+        print(f"  - Try: python batch_process.py")
+        print(f"  - Adjust parameters in config.json for better results")
+
+    else:
+        print("\nDemo failed. Please check your Python environment and dependencies.")
+
+
+if __name__ == "__main__":
+    main()