Update app.py

app.py

@@ -4,7 +4,7 @@ from PIL import Image
 from diffusers import AutoPipelineForText2Image, DDIMScheduler
 import numpy as np
 from torchvision import transforms
-import spaces  # Make sure to import spaces
+import spaces
 
 # Initialize the pipeline
 pipeline = AutoPipelineForText2Image.from_pretrained(
@@ -47,10 +47,10 @@ def transform_image(face_image):
     if processed_face_image.mode == 'L':
         processed_face_image = processed_face_image.convert('RGB')
     
-    # Resize the face image
+    # 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 and convert to tensor
+    # 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_tensor = transforms.ToTensor()(style_image).unsqueeze(0).to("cuda")
@@ -81,4 +81,4 @@ demo = gr.Interface(
 )
 
 demo.queue(max_size=20)
-demo.launch()
+demo.launch()