Update app.py

app.py

@@ -43,22 +43,21 @@ def transform_image(face_image):
     else:
         raise ValueError("Unsupported image format")
     
-    # Convert the processed face image to RGB format if it has only 1 channel
-    if processed_face_image.mode == 'L':
-        processed_face_image = processed_face_image.convert('RGB')
+    # Ensure the processed face image is in RGB format
+    processed_face_image = processed_face_image.convert('RGB')
     
     # Resize the face image to 1024x1024
     processed_face_image = processed_face_image.resize(desired_size, Image.LANCZOS)
 
     # Load the style image from the local path, resize it to 1024x1024, and convert to tensor
     style_image_path = "examples/soyjak2.jpg"  # Ensure this path is correct
-    style_image = Image.open(style_image_path).resize(desired_size, Image.LANCZOS)
+    style_image = Image.open(style_image_path).resize(desired_size, Image.LANCZOS).convert('RGB')
     style_image_tensor = transforms.ToTensor()(style_image).unsqueeze(0).to("cuda")
 
     # Perform the transformation using the configured pipeline
     image = pipeline(
         prompt="soyjak",
-        ip_adapter_image=[style_image_tensor, processed_face_image],  # Ensure these are tensors
+        ip_adapter_image=[style_image_tensor, transforms.ToTensor()(processed_face_image).unsqueeze(0).to("cuda")],  # Ensure these are tensors
         negative_prompt="monochrome, lowres, bad anatomy, worst quality, low quality",
         num_inference_steps=30,
         generator=generator,