Create app.py

app.py

@@ -0,0 +1,22 @@
+import numpy as np
+import gradio as gr
+import tensorflow as tf
+from tensorflow import keras
+import pandas as pd
+
+model = tf.keras.models.load_model("Oxygen Content.keras")
+
+def predict(Fuel,Air):
+    Fuel = (Fuel*1700)/17000
+    Air = (Air*13000)/130000
+    xn = np.array([[Fuel,Air]])
+    yn = abs(model.predict(xn))
+    Percantage = np.round(yn[0,0]*100, 2)
+    return Percantage
+
+demo = gr.Interface(fn=predict,inputs=["number", "number"],outputs=["number"],
+                   title="Oxygen Content(%) Analyzer in Flue Gas",
+                    description="Input Fuel Flowrate and Air Flowrate as per controller recorder value for example: 2.2 or 5.5 etc. This model will predict the Oxygen Content(%) in Flue Gas just like real life analyzer.",
+                   )
+
+demo.launch(share=True)