fix: image alpha error

app/api/v1/endpoints/image.py

@@ -35,12 +35,10 @@ async def process_image_ocr(
     )
 
     try:
-        # 3. Perform OCR based on layout
         ocr_result = ocr_service.recognize(image)
     except RuntimeError as e:
         raise HTTPException(status_code=503, detail=str(e))
 
-    # 4. Return response
     return ImageOCRResponse(
         latex=ocr_result.get("latex", ""),
         markdown=ocr_result.get("markdown", ""),

app/main.py

@@ -33,6 +33,7 @@ app = FastAPI(
 app.include_router(api_router, prefix=settings.api_prefix)
 
 
+
 @app.get("/health")
 async def health_check():
     """Health check endpoint."""

app/services/image_processor.py

@@ -25,6 +25,38 @@ class ImageProcessor:
         """
         self.padding_ratio = padding_ratio or settings.image_padding_ratio
 
+    def _convert_to_bgr(self, pil_image: Image.Image) -> np.ndarray:
+        """Convert PIL Image to BGR numpy array, handling alpha channel.
+
+        Args:
+            pil_image: PIL Image object.
+
+        Returns:
+            Image as numpy array in BGR format.
+        """
+        # Handle RGBA images (PNG with transparency)
+        if pil_image.mode == "RGBA":
+            # Create white background and paste image on top
+            background = Image.new("RGB", pil_image.size, (255, 255, 255))
+            background.paste(pil_image, mask=pil_image.split()[3])  # Use alpha as mask
+            pil_image = background
+        elif pil_image.mode == "LA":
+            # Grayscale with alpha
+            background = Image.new("L", pil_image.size, 255)
+            background.paste(pil_image, mask=pil_image.split()[1])
+            pil_image = background.convert("RGB")
+        elif pil_image.mode == "P":
+            # Palette mode, may have transparency
+            pil_image = pil_image.convert("RGBA")
+            background = Image.new("RGB", pil_image.size, (255, 255, 255))
+            background.paste(pil_image, mask=pil_image.split()[3])
+            pil_image = background
+        elif pil_image.mode != "RGB":
+            # Convert other modes to RGB
+            pil_image = pil_image.convert("RGB")
+
+        return cv2.cvtColor(np.array(pil_image), cv2.COLOR_RGB2BGR)
+
     def load_image_from_url(self, url: str) -> np.ndarray:
         """Load image from URL.
 
@@ -40,8 +72,8 @@ class ImageProcessor:
         try:
             with urlopen(url, timeout=30) as response:
                 image_data = response.read()
-            image = Image.open(io.BytesIO(image_data))
+            pil_image = Image.open(io.BytesIO(image_data))
-            return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+            return self._convert_to_bgr(pil_image)
         except Exception as e:
             raise ValueError(f"Failed to load image from URL: {e}") from e
 
@@ -63,8 +95,8 @@ class ImageProcessor:
                 base64_str = base64_str.split(",", 1)[1]
 
             image_data = base64.b64decode(base64_str)
-            image = Image.open(io.BytesIO(image_data))
+            pil_image = Image.open(io.BytesIO(image_data))
-            return cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+            return self._convert_to_bgr(pil_image)
         except Exception as e:
             raise ValueError(f"Failed to decode base64 image: {e}") from e
 

app/services/layout_detector.py

@@ -140,18 +140,39 @@ class LayoutDetector:
 
 if __name__ == "__main__":
     import cv2
+    from app.core.config import get_settings
     from app.services.image_processor import ImageProcessor
-
+    from app.services.converter import Converter
+    from app.services.ocr_service import OCRService
+    
+    settings = get_settings()
+    
+    # Initialize dependencies
     layout_detector = LayoutDetector()
-    image_path = "test/timeout.png"
+    image_processor = ImageProcessor(padding_ratio=settings.image_padding_ratio)
-
+    converter = Converter()
+    
+    # Initialize OCR service
+    ocr_service = OCRService(
+        vl_server_url=settings.paddleocr_vl_url,
+        layout_detector=layout_detector,
+        image_processor=image_processor,
+        converter=converter,
+    )
+    
+    # Load test image
+    image_path = "test/complex_formula.png"
     image = cv2.imread(image_path)
-    image_processor = ImageProcessor(padding_ratio=0.15)
+    
-    image = image_processor.add_padding(image)
+    if image is None:
-
+        print(f"Failed to load image: {image_path}")
-    # Save the padded image for debugging
+    else:
-    cv2.imwrite("debug_padded_image.png", image)
+        print(f"Image loaded: {image.shape}")
-
+        
-
+        # Run OCR recognition
-    layout_info = layout_detector.detect(image)
+        result = ocr_service.recognize(image)
-    print(layout_info)
+        
+        print("\n=== OCR Result ===")
+        print(f"Markdown:\n{result['markdown']}")
+        print(f"\nLaTeX:\n{result['latex']}")
+        print(f"\nMathML:\n{result['mathml']}")

app/services/ocr_service.py

@@ -35,6 +35,7 @@ class OCRService:
         self.layout_detector = layout_detector 
         self.image_processor = image_processor
         self.converter = converter
+
     def _get_pipeline(self):    
         """Get or create PaddleOCR-VL pipeline.
 
@@ -127,15 +128,3 @@ class OCRService:
             return self.recognize_mixed(image)
         else:
             return self.recognize_formula(image)
-
-
-if __name__ == "__main__":
-    import cv2
-    from app.services.image_processor import ImageProcessor
-    from app.services.layout_detector import LayoutDetector
-    image_processor = ImageProcessor(padding_ratio=0.15)
-    layout_detector = LayoutDetector()
-    ocr_service = OCRService(image_processor=image_processor, layout_detector=layout_detector)
-    image = cv2.imread("test/image.png")
-    ocr_result = ocr_service.recognize(image)
-    print(ocr_result)