Create app.py

app.py

@@ -0,0 +1,20 @@
+import gradio as gr
+from huggingface_hub import from_pretrained_keras
+
+def predict_diagnosis(loops):
+  loops_arr = tf.keras.utils.img_to_array(loops)
+  #new_loops_arr = np.array(loops)
+  new_img = tf.expand_dims(loops_arr,0)
+  model = from_pretrained_keras("layai/priya-loop-model")
+  single_data = model.predict(new_img)
+  single_data = single_data[0]
+  return np.argmax(single_data)
+
+input = gr.inputs.Image(shape=(906, 255))
+output = gr.outputs.Textbox(label='Predicted diagnosis')
+iloops = gr.Interface( fn=predict_diagnosis,
+              inputs=input,
+              outputs=output,
+              capture_session=True)
+
+iloops.launch()