init repo

app/services/image_processor.py

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+"""Image preprocessing service using OpenCV."""
+
+import base64
+import io
+from urllib.request import urlopen
+
+import cv2
+import numpy as np
+from PIL import Image
+
+from app.core.config import get_settings
+
+settings = get_settings()
+
+
+class ImageProcessor:
+    """Service for image preprocessing operations."""
+
+    def __init__(self, padding_ratio: float | None = None):
+        """Initialize with padding ratio.
+
+        Args:
+            padding_ratio: Ratio for padding on each side (default from settings).
+                          0.15 means 15% padding on each side = 30% total expansion.
+        """
+        self.padding_ratio = padding_ratio or settings.image_padding_ratio
+
+    def load_image_from_url(self, url: str) -> np.ndarray:
+        """Load image from URL.
+
+        Args:
+            url: Image URL to fetch.
+
+        Returns:
+            Image as numpy array in BGR format.
+
+        Raises:
+            ValueError: If image cannot be loaded from URL.
+        """
+        try:
+            with urlopen(url, timeout=30) as response:
+                image_data = response.read()
+            image = Image.open(io.BytesIO(image_data))
+            return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+        except Exception as e:
+            raise ValueError(f"Failed to load image from URL: {e}") from e
+
+    def load_image_from_base64(self, base64_str: str) -> np.ndarray:
+        """Load image from base64 string.
+
+        Args:
+            base64_str: Base64-encoded image data.
+
+        Returns:
+            Image as numpy array in BGR format.
+
+        Raises:
+            ValueError: If image cannot be decoded.
+        """
+        try:
+            # Handle data URL format
+            if "," in base64_str:
+                base64_str = base64_str.split(",", 1)[1]
+
+            image_data = base64.b64decode(base64_str)
+            image = Image.open(io.BytesIO(image_data))
+            return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+        except Exception as e:
+            raise ValueError(f"Failed to decode base64 image: {e}") from e
+
+    def add_padding(self, image: np.ndarray) -> np.ndarray:
+        """Add whitespace padding around the image.
+
+        Adds padding equal to padding_ratio * max(height, width) on each side.
+        This expands the image by approximately 30% total (15% on each side).
+
+        Args:
+            image: Input image as numpy array in BGR format.
+
+        Returns:
+            Padded image as numpy array.
+        """
+        height, width = image.shape[:2]
+        padding = int(max(height, width) * self.padding_ratio)
+
+        # Add white padding on all sides
+        padded_image = cv2.copyMakeBorder(
+            image,
+            top=padding,
+            bottom=padding,
+            left=padding,
+            right=padding,
+            borderType=cv2.BORDER_CONSTANT,
+            value=[255, 255, 255],  # White
+        )
+
+        return padded_image
+
+    def preprocess(self, image_url: str | None, image_base64: str | None) -> np.ndarray:
+        """Load and preprocess image with padding.
+
+        Args:
+            image_url: URL to fetch image from (optional).
+            image_base64: Base64-encoded image (optional).
+
+        Returns:
+            Preprocessed image with padding.
+
+        Raises:
+            ValueError: If neither input is provided or loading fails.
+        """
+        if image_url:
+            image = self.load_image_from_url(image_url)
+        elif image_base64:
+            image = self.load_image_from_base64(image_base64)
+        else:
+            raise ValueError("Either image_url or image_base64 must be provided")
+
+        return self.add_padding(image)
+
+    def image_to_base64(self, image: np.ndarray, format: str = "PNG") -> str:
+        """Convert numpy image to base64 string.
+
+        Args:
+            image: Image as numpy array in BGR format.
+            format: Output format (PNG, JPEG).
+
+        Returns:
+            Base64-encoded image string.
+        """
+        image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+        pil_image = Image.fromarray(image_rgb)
+
+        buffer = io.BytesIO()
+        pil_image.save(buffer, format=format)
+        buffer.seek(0)
+
+        return base64.b64encode(buffer.getvalue()).decode("utf-8")
+