Update app.py

app.py

@@ -64,15 +64,27 @@ class ForgeryDetector:
     
     def detect(self, image):
         """
-        Detect forgeries in document image
+        Detect forgeries in document image or PDF
         
         Args:
-            image: PIL Image or numpy array
+            image: PIL Image, numpy array, or path to PDF file
             
         Returns:
             overlay_image: Image with detection overlay
             results_json: Detection results as JSON
         """
+        # Handle PDF files
+        if isinstance(image, str) and image.lower().endswith('.pdf'):
+            import fitz  # PyMuPDF
+            # Open PDF and convert first page to image
+            pdf_document = fitz.open(image)
+            page = pdf_document[0]  # First page
+            pix = page.get_pixmap(matrix=fitz.Matrix(2, 2))  # 2x scale for better quality
+            image = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.height, pix.width, pix.n)
+            if pix.n == 4:  # RGBA
+                image = cv2.cvtColor(image, cv2.COLOR_RGBA2RGB)
+            pdf_document.close()
+        
         # Convert PIL to numpy
         if isinstance(image, Image.Image):
             image = np.array(image)
@@ -197,26 +209,47 @@ class ForgeryDetector:
 detector = ForgeryDetector()
 
 
-def detect_forgery(image):
+def detect_forgery(file):
     """Gradio interface function"""
     try:
-        overlay, results = detector.detect(image)
+        if file is None:
+            return None, {"error": "No file uploaded"}
+        
+        # Get file path
+        file_path = file.name if hasattr(file, 'name') else file
+        
+        # Check if PDF
+        if file_path.lower().endswith('.pdf'):
+            # Pass PDF path directly to detector
+            overlay, results = detector.detect(file_path)
+        else:
+            # Load image and pass to detector
+            image = Image.open(file_path)
+            overlay, results = detector.detect(image)
+        
         return overlay, results  # Return dict directly, not json.dumps
     except Exception as e:
-        return None, {"error": str(e)}
+        import traceback
+        error_details = traceback.format_exc()
+        print(f"Error: {error_details}")
+        return None, {"error": str(e), "details": error_details}
 
 
 # Create Gradio interface
 demo = gr.Interface(
     fn=detect_forgery,
-    inputs=gr.Image(type="pil", label="Upload Document Image"),
+    inputs=gr.File(label="Upload Document (Image or PDF)", file_types=["image", ".pdf"]),
     outputs=[
         gr.Image(type="numpy", label="Detection Result"),
         gr.JSON(label="Detection Details")
     ],
     title="📄 Document Forgery Detector",
     description="""
-    Upload a document image to detect and classify forgeries.
+    Upload a document image or PDF to detect and classify forgeries.
+    
+    **Supported Formats:**
+    - 📷 Images: JPG, PNG, BMP, TIFF, WebP
+    - 📄 PDF: First page will be analyzed
     
     **Supported Forgery Types:**
     - 🔴 Copy-Move: Duplicated regions within the document