Initial commit — PlantGuideScraper project

backend/app/utils/image_quality.py

@@ -0,0 +1,109 @@
+"""Image quality assessment utilities."""
+
+import numpy as np
+from PIL import Image as PILImage
+from scipy import ndimage
+
+
+def calculate_blur_score(image_path: str) -> float:
+    """
+    Calculate blur score using Laplacian variance.
+    Higher score = sharper image.
+
+    Args:
+        image_path: Path to image file
+
+    Returns:
+        Variance of Laplacian (higher = sharper)
+    """
+    try:
+        img = PILImage.open(image_path).convert("L")
+        img_array = np.array(img)
+        laplacian = ndimage.laplace(img_array)
+        return float(np.var(laplacian))
+    except Exception:
+        return 0.0
+
+
+def is_too_blurry(image_path: str, threshold: float = 100.0) -> bool:
+    """
+    Check if image is too blurry for training.
+
+    Args:
+        image_path: Path to image file
+        threshold: Minimum acceptable blur score (default 100)
+
+    Returns:
+        True if image is too blurry
+    """
+    score = calculate_blur_score(image_path)
+    return score < threshold
+
+
+def get_image_dimensions(image_path: str) -> tuple[int, int]:
+    """
+    Get image dimensions.
+
+    Args:
+        image_path: Path to image file
+
+    Returns:
+        Tuple of (width, height)
+    """
+    try:
+        with PILImage.open(image_path) as img:
+            return img.size
+    except Exception:
+        return (0, 0)
+
+
+def is_too_small(image_path: str, min_size: int = 256) -> bool:
+    """
+    Check if image is too small for training.
+
+    Args:
+        image_path: Path to image file
+        min_size: Minimum dimension size (default 256)
+
+    Returns:
+        True if image is too small
+    """
+    width, height = get_image_dimensions(image_path)
+    return width < min_size or height < min_size
+
+
+def resize_image(
+    image_path: str,
+    output_path: str = None,
+    max_size: int = 512,
+    quality: int = 95,
+) -> bool:
+    """
+    Resize image to max dimension while preserving aspect ratio.
+
+    Args:
+        image_path: Path to input image
+        output_path: Path for output (defaults to overwriting input)
+        max_size: Maximum dimension size (default 512)
+        quality: JPEG quality (default 95)
+
+    Returns:
+        True if successful
+    """
+    try:
+        output_path = output_path or image_path
+
+        with PILImage.open(image_path) as img:
+            # Only resize if larger than max_size
+            if max(img.size) > max_size:
+                img.thumbnail((max_size, max_size), PILImage.Resampling.LANCZOS)
+
+            # Convert to RGB if necessary (for JPEG)
+            if img.mode in ("RGBA", "P"):
+                img = img.convert("RGB")
+
+            img.save(output_path, "JPEG", quality=quality)
+
+        return True
+    except Exception:
+        return False