Update forensics/ela_hybrid.py

forensics/ela_hybrid.py

@@ -61,20 +61,20 @@ def visualize_hybrid(hybrid_array: np.ndarray):
     ela_image = Image.fromarray((hybrid_array[:, :, 3:] * 255).astype(np.uint8))
 
     return [rgb_image, ela_image]
+    # ela_hybrid.py
     
-def generate_hybrid_ela_func(img_np_og, description, quality=95, scale_factor=150):
+def generate_hybrid_ela_func(img_input):
     """
-    Returns a list of two PIL Images: one for RGB, one for ELA map.
-    This matches the structure of other forensic tools.
+    Returns a list of 2 PIL Images: [Original RGB Image, Hybrid ELA Output].
     """
     from PIL import Image
+    import numpy as np
 
-    # Ensure the image is in RGB numpy format
-    if img_np_og.ndim == 2:
-        img_np_og = cv2.cvtColor(img_np_og, cv2.COLOR_GRAY2RGB)
+    # Convert input to numpy array if needed
+    if not isinstance(img_input, np.ndarray):
+        img_input = np.array(img_input)  # Ensure numpy format
 
-    hybrid_array = generate_ela_hybrid(img_np_og, quality=quality, scale_factor=scale_factor)
+    # Generate ELA
+    hybrid_array = generate_ela_hybrid(img_input, quality=75, scale_factor=100)
     visualizations = visualize_hybrid(hybrid_array)
-    
-    # Return list of PIL Images for Gradio compatibility
-    return visualizations
+    return list(visualizations)  # Returns [RGB PIL Image, ELA PIL Image]