init

src/utils.py

@@ -0,0 +1,98 @@
+"""
+Utility functions for data augmentation
+"""
+import os
+import logging
+from pathlib import Path
+from typing import List, Tuple, Optional
+import cv2
+import numpy as np
+from PIL import Image
+
+def setup_logging(log_level: str = "INFO") -> logging.Logger:
+    """Setup logging configuration"""
+    logging.basicConfig(
+        level=getattr(logging, log_level.upper()),
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+        handlers=[
+            logging.FileHandler('data_augmentation.log'),
+            logging.StreamHandler()
+        ]
+    )
+    return logging.getLogger(__name__)
+
+def get_image_files(directory: Path) -> List[Path]:
+    """Get all image files from directory"""
+    SUPPORTED_FORMATS = ['.jpg', '.jpeg', '.png', '.bmp', '.tiff']
+    
+    image_files = []
+    if directory.exists():
+        for ext in SUPPORTED_FORMATS:
+            image_files.extend(directory.glob(f"*{ext}"))
+            image_files.extend(directory.glob(f"*{ext.upper()}"))
+    return sorted(image_files)
+
+def validate_image(image_path: Path) -> bool:
+    """Validate if file is a valid image"""
+    try:
+        with Image.open(image_path) as img:
+            img.verify()
+        return True
+    except Exception:
+        return False
+
+def load_image(image_path: Path, target_size: Tuple[int, int] = None) -> Optional[np.ndarray]:
+    """Load and resize image"""
+    try:
+        # Load image using OpenCV
+        image = cv2.imread(str(image_path))
+        if image is None:
+            return None
+        
+        # Convert BGR to RGB
+        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+        
+        # Resize if target_size is provided
+        if target_size:
+            image = cv2.resize(image, target_size, interpolation=cv2.INTER_AREA)
+        
+        return image
+    except Exception as e:
+        print(f"Error loading image {image_path}: {e}")
+        return None
+
+def save_image(image: np.ndarray, output_path: Path, quality: int = 95) -> bool:
+    """Save image to file"""
+    try:
+        # Convert RGB to BGR for OpenCV
+        image_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+        
+        # Create output directory if it doesn't exist
+        output_path.parent.mkdir(parents=True, exist_ok=True)
+        
+        # Save image
+        cv2.imwrite(str(output_path), image_bgr, [cv2.IMWRITE_JPEG_QUALITY, quality])
+        return True
+    except Exception as e:
+        print(f"Error saving image {output_path}: {e}")
+        return False
+
+def create_augmented_filename(original_path: Path, index: int, suffix: str = "aug") -> Path:
+    """Create filename for augmented image"""
+    stem = original_path.stem
+    suffix = f"_{suffix}_{index:02d}"
+    return original_path.parent / f"{stem}{suffix}{original_path.suffix}"
+
+def get_file_size_mb(file_path: Path) -> float:
+    """Get file size in MB"""
+    return file_path.stat().st_size / (1024 * 1024)
+
+def print_progress(current: int, total: int, prefix: str = "Progress"):
+    """Print progress bar"""
+    bar_length = 50
+    filled_length = int(round(bar_length * current / float(total)))
+    percents = round(100.0 * current / float(total), 1)
+    bar = '=' * filled_length + '-' * (bar_length - filled_length)
+    print(f'\r{prefix}: [{bar}] {percents}% ({current}/{total})', end='')
+    if current == total:
+        print()