resize images

app.py

@@ -145,6 +145,15 @@ def style_transfer(content_image, style_image, alpha, beta, conv1_1, conv2_1, co
     
     return im_convert(target)
 
+
+# Function to resize image while maintaining aspect ratio
+def resize_image(image_path, max_size=400):
+    img = Image.open(image_path).convert('RGB')
+    ratio = max_size / max(img.size)
+    new_size = tuple([int(x*ratio) for x in img.size])
+    img = img.resize(new_size, Image.ANTIALIAS)
+    return np.array(img)
+
 # Example images
 examples = [
     ["https://huggingface.co/spaces/muneebable/vgg-style-transfer/resolve/main/assets/content_1.jpg",
@@ -163,13 +172,16 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 vgg.to(device)
 
 
+# Resize example images
+resized_examples = [[resize_image(content), resize_image(style)] for content, style in examples]
+
 # Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# Neural Style Transfer")
     with gr.Row():
         with gr.Column():
-            content_input = gr.Image(label="Content Image")
-            style_input = gr.Image(label="Style Image")
+            content_input = gr.Image(label="Content Image", type="numpy", image_mode="RGB", shape=(400, 400))
+            style_input = gr.Image(label="Style Image", type="numpy", image_mode="RGB", shape=(400, 400))
         with gr.Column():
             output_image = gr.Image(label="Output Image")
     
@@ -206,7 +218,7 @@ with gr.Blocks() as demo:
     )
     
     gr.Examples(
-        examples,
+        resized_examples,
         inputs=[content_input, style_input]
     )