add- fit to image

runway.py

@@ -31,14 +31,6 @@ def prepare_guided_image(original_image: Image, reference_image: Image, mask_ima
     Prepare an initial image by softly blending the reference image into the masked area.
     - Areas to keep (black in mask, 0) remain fully from the original image.
     - Areas to inpaint (white in mask, 255) take content from the reference image with soft blending.
-    
-    Args:
-        original_image (Image): The original image (RGB).
-        reference_image (Image): The reference image to copy from (RGB).
-        mask_image (Image): The mask image (grayscale, L mode).
-    
-    Returns:
-        Image: The blended image to guide inpainting.
     """
     original_array = np.array(original_image)
     reference_array = np.array(reference_image)
@@ -80,6 +72,10 @@ def fit_image_to_mask(original_image: Image, reference_image: Image, mask_x1: in
     mask_width = mask_x2 - mask_x1
     mask_height = mask_y2 - mask_y1
 
+    # Ensure mask dimensions are positive
+    if mask_width <= 0 or mask_height <= 0:
+        raise ValueError("Mask dimensions must be positive")
+
     # Resize reference image to fit the mask while preserving aspect ratio
     ref_width, ref_height = reference_image.size
     aspect_ratio = ref_width / ref_height
@@ -195,13 +191,6 @@ async def fit_image_to_mask(
 ):
     """
     Endpoint for fitting a reference image into a masked region of the original image, refined to look natural.
-    - `image`: Original image file (PNG/JPG), e.g., a table.
-    - `reference_image`: Image to fit into the masked region (PNG/JPG), e.g., a cat.
-    - `prompt`: Text prompt for inpainting refinement.
-    - `mask_x1, mask_y1, mask_x2, mask_y2`: Coordinates for the rectangular mask (default: 100,100 to 200,200).
-    
-    Returns:
-    - The resulting image as a PNG file.
     """
     try:
         # Load the uploaded images
@@ -211,7 +200,10 @@ async def fit_image_to_mask(
         reference_image = Image.open(io.BytesIO(reference_bytes)).convert("RGB")
 
         # Fit the reference image into the masked region
-        guided_image, mask_image = fit_image_to_mask(original_image, reference_image, mask_x1, mask_y1, mask_x2, mask_y2)
+        result = fit_image_to_mask(original_image, reference_image, mask_x1, mask_y1, mask_x2, mask_y2)
+        if not isinstance(result, tuple) or len(result) != 2:
+            raise ValueError(f"Expected tuple of (guided_image, mask_image), got {type(result)}")
+        guided_image, mask_image = result
 
         # Soften the mask for smoother transitions
         softened_mask = soften_mask(mask_image, softness=5)
@@ -234,8 +226,10 @@ async def fit_image_to_mask(
             media_type="image/png",
             headers={"Content-Disposition": "attachment; filename=fitted_image.png"}
         )
+    except ValueError as ve:
+        raise HTTPException(status_code=500, detail=f"ValueError in processing: {str(ve)}")
     except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Error during fitting and inpainting: {e}")
+        raise HTTPException(status_code=500, detail=f"Error during fitting and inpainting: {str(e)}")
 
 if __name__ == "__main__":
     import uvicorn