Update app.py

app.py

@@ -1,7 +1,35 @@
 import gradio as gr
+from fastai.vision.all import *
+import skimage
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load your trained model
+learn = load_learner('export.pkl')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+# Define the labels (in this case, just 'cat' and 'dog')
+labels = ['cat', 'dog']
+
+# Define the prediction function
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    # Return a dictionary of probabilities
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+# Update the title, description, and other details for your cat vs. dog classifier
+title = "Cat vs Dog Classifier"
+description = "A classifier to distinguish between cats and dogs. Trained with fastai on a relevant dataset."
+article = "<p style='text-align: center'><a href='https://yourlinkhere.com' target='_blank'>Blog post or additional information</a></p>"
+examples = ['/path/to/example_image.jpg'] # Update this path to your example images
+
+# Create and launch the Gradio interface
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Image(shape=(512, 512)),
+    outputs=gr.outputs.Label(num_top_classes=2),
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    interpretation='default',
+    enable_queue=True
+).launch()