feat: Add optimize command

- Add whitespace trimming functionality
- Add optional PNG optimization with optipng
- Add progress tracking and error handling
- Improve imports organization
- Add proper docstrings and return values

pdf_cleaner.py

@@ -1,11 +1,16 @@
-import os
 #!/usr/bin/env -S uv run
+
+import os
+import shutil
+import subprocess
+from pathlib import Path
+from typing import List, Tuple
+
 import click
 import cv2
-import numpy as np
-from PIL import Image
-from pdf2image import convert_from_path
 import img2pdf
+import numpy as np
+from pdf2image import convert_from_path
 
 def ensure_temp_dir():
     """Ensure temporary directory exists and return its path."""
@@ -117,6 +122,125 @@ def deskew():
         else:
             print("  No line segments detected")
 
+def trim_whitespace(image_path: str) -> bool:
+    """Remove white space from around the image.
+    
+    Returns:
+        bool: True if successful, False otherwise
+    """
+    try:
+        # Read the image
+        img = cv2.imread(image_path)
+        if img is None:
+            print(f"Warning: Could not read image {image_path}")
+            return False
+        
+        # Convert to grayscale
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        
+        # Threshold the image
+        _, thresh = cv2.threshold(gray, 250, 255, cv2.THRESH_BINARY_INV)
+        
+        # Find non-zero points
+        coords = cv2.findNonZero(thresh)
+        if coords is None:
+            print(f"Warning: No content found in {image_path}")
+            return False
+        
+        # Get bounding rectangle
+        x, y, w, h = cv2.boundingRect(coords)
+        
+        # Add small padding (20 pixels)
+        padding = 20
+        height, width = img.shape[:2]
+        x = max(0, x - padding)
+        y = max(0, y - padding)
+        w = min(width - x, w + 2 * padding)
+        h = min(height - y, h + 2 * padding)
+        
+        # Crop the image
+        cropped = img[y:y+h, x:x+w]
+        
+        # Save the cropped image
+        cv2.imwrite(image_path, cropped)
+        return True
+    except Exception as e:
+        print(f"Error processing {image_path}: {str(e)}")
+        return False
+
+def check_optipng_installed() -> bool:
+    """Check if optipng is installed."""
+    try:
+        result = subprocess.run(['optipng', '-v'], capture_output=True, text=True)
+        return result.returncode == 0
+    except FileNotFoundError:
+        return False
+
+def run_optipng(file_path: str) -> bool:
+    """Run optipng on a file with error handling.
+    
+    Returns:
+        bool: True if successful, False otherwise
+    """
+    try:
+        result = subprocess.run(
+            ['optipng', '-o7', file_path],
+            capture_output=True,
+            text=True,
+            check=True
+        )
+        return True
+    except subprocess.CalledProcessError as e:
+        print(f"Error optimizing {file_path}: {e.stderr}")
+        return False
+    except Exception as e:
+        print(f"Unexpected error optimizing {file_path}: {str(e)}")
+        return False
+
+@cli.command()
+def optimize():
+    """Optimize images by trimming whitespace and optionally running optipng."""
+    temp_dir = ensure_temp_dir()
+    temp_files = get_temp_files()
+    if not temp_files:
+        print("No pages found in temporary directory. Run 'extract' first.")
+        return
+    
+    total_files = len(temp_files)
+    successful_trims = 0
+    successful_opts = 0
+    
+    print(f"Processing {total_files} images...")
+    
+    # Trim whitespace
+    print("\nTrimming whitespace from images...")
+    for i, file_path in enumerate(temp_files, 1):
+        print(f"[{i}/{total_files}] Processing {os.path.basename(file_path)}...", end='', flush=True)
+        if trim_whitespace(file_path):
+            successful_trims += 1
+            print(" ")
+        else:
+            print(" ")
+    
+    # Optimize with optipng if available
+    if check_optipng_installed():
+        print("\nOptimizing PNG files with optipng...")
+        for i, file_path in enumerate(temp_files, 1):
+            print(f"[{i}/{total_files}] Optimizing {os.path.basename(file_path)}...", end='', flush=True)
+            if run_optipng(file_path):
+                successful_opts += 1
+                print(" ")
+            else:
+                print(" ")
+    else:
+        print("\nNote: optipng not found. Skipping PNG optimization.")
+    
+    # Print summary
+    print("\nOptimization complete!")
+    print(f"Successfully trimmed: {successful_trims}/{total_files} images")
+    if check_optipng_installed():
+        print(f"Successfully optimized: {successful_opts}/{total_files} images")
+
 @cli.command()
 @click.argument('output_pdf', type=click.Path())
 def finalize(output_pdf):