Create app.py

app.py

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+# Import the necessary libraries
+from fastai.vision.all import *
+import gradio as gr
+
+# Load the trained model
+learn = load_learner('export.pkl')
+
+# Get the labels from the model's dataloader
+labels = learn.dls.vocab
+
+# Function to classify an image using the model
+def classify_image(img):
+    pred,pred_idx,probs = learn.predict(img)
+    return dict(zip(labels, probs))
+
+
+# Create the Gradio interface
+image_input = gr.components.Image()
+label_output = gr.components.Label()
+
+examples = [f"assets/{fn}" for fn in ["bergen.jpg", "oslo.jpg", "newyork.jpg"]]
+
+iface = gr.Interface(
+    fn=classify_image, 
+    inputs=image_input, 
+    outputs=label_output, 
+    examples=examples
+    )
+
+iface.launch(inline=False)