Create app.py

app.py

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+import gradio as gr
+
+
+
+def classify_image(inp):
+  new_image = np.zeros((120, 120, 4))
+
+# Copy the original image to the first three channels of the new array
+  new_image[:,:,0:3] = inp[:,:,:]
+
+  model = tf.keras.models.load_model('poke.h5')
+  prediction=np.argmax(model.predict(np.expand_dims(new_image,axis=0)))
+  prediction=int(prediction)
+  if prediction==1:
+    return "Water"
+  else:
+    return "Fire"
+
+
+
+gr.Interface(fn=classify_image, 
+             inputs=gr.Image(shape=(120,120)),
+             outputs=gr.Label(),
+            
+             ).launch()