Create app.py

created an app file

app.py

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+## libraries for data preprocessing
+import numpy as np 
+import pandas as pd 
+
+## libraries for training dl models
+import tensorflow as tf
+from tensorflow import keras 
+
+## libraries for pre-trained neural network
+from tensorflow.keras.applications.xception import preprocess_input
+
+## libraries for loading batch images
+from tensorflow.keras.preprocessing.image import load_img
+
+import gradio as gr 
+
+def get_y(o):
+  return [parent_label(o)]
+  
+## lets load the model 
+model = keras.models.load_model('xception_v1_15_0.812.h5')
+
+
+
+def maize_disease_classifier(image):
+    x = np.array(image)
+    X = np.array([x])
+    X = preprocess_input(X)
+    pred = model.predict(X)
+    result = pred[0].argmax()
+    ## lets create our labels
+    labels = {
+        0: 'maize ear rot',
+        1: 'maize fall armyworm',
+        2: 'maize stem borer'
+    }
+
+    label = labels[pred[0].argmax()]
+    return pred, result, label
+    
+   
+iface = gr.Interface(fn=maize_disease_classifier, inputs=gr.inputs.Image(shape=(224, 224)), \
+             outputs=["number", "number", "text"])
+
+iface.launch(inline=False)