Create app.py

app.py

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+import gradio as gr
+import pickle
+import os
+from fastai.vision.all import load_learner
+
+with open("list.dat", 'rb') as f:
+    categories = pickle.load(f)
+    
+model = load_learner("model.pkl")
+
+def predict(img):
+    pred, idx, probs = model.predict(img)
+    dict1 = dict(zip(categories, map(float, preds)))
+    dict1 = dict(sorted(dict1.items(), key=lambda item : item[1]))
+    output = {key:dict1[key] for key in dict1.keys()[-3:]}
+    sum = 0
+    for i in dict1.keys()[-3:]:
+        sum += dict1[i]
+    output.update("Other", 1.0 - sum)
+    return output
+
+image = gr.inputs.Image(shape=(264, 264))
+label = gr.outputs.Label()
+examples = ["cherry_leaf.jpg", "frogeye_spots_apple_leaf.jpg", "apple_leaf.jpg"]
+examples = [os.path.join("images", example) for example in examples]
+
+interface = gr.Interface(fn=predict, inputs=image, outputs=label, examples=examples)
+interface.launch()