Create app.py

app.py

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+from tensorflow import keras
+import gradio as gr
+
+path_to_model = "/content/drive/MyDrive/modelPredict.h5"
+
+model = keras.models.load_model(path_to_model)
+
+def classify_image(inp):
+    # inp = load_image(inp_path)
+    inp = inp.reshape((-1, 224, 224, 3))
+    prediction = model.predict(inp).tolist()[0]
+    class_names = ['Bacterialblight', 'Blast', 'Brownspot', 'Tungro']
+    return {class_names[i]: prediction[i] for i in range(4)}
+
+gr.Interface(fn=classify_image, 
+             inputs=gr.inputs.Image(shape=(224, 224)),
+             outputs=gr.outputs.Label(num_top_classes=4),
+             ).launch(debug=True)