Create app.py

app.py

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+import torch
+import gradio as gr
+from PIL import Image
+from torchvision import transforms
+
+# Load the pre-trained gram matrix
+gram_matrix = torch.load("path_to_gram_matrix.pt")
+
+def style_transfer(content_image):
+    # Preprocess the content image
+    preprocess = transforms.Compose([
+        transforms.Resize((256, 256)),
+        transforms.ToTensor(),
+        transforms.Lambda(lambda x: x.unsqueeze(0))  
+    ])
+    content_image = preprocess(content_image)
+    
+    # Apply style transfer using the pre-trained gram matrix
+    output_image = apply_style_transfer(content_image, gram_matrix)
+    
+    # Convert tensor to PIL image for display
+    output_image = transforms.ToPILImage()(output_image.squeeze(0))
+    return output_image
+
+# Define Gradio interface
+iface = gr.Interface(fn=style_transfer, 
+                     inputs=gr.inputs.Image(), 
+                     outputs="image")
+
+iface.launch()