Create app.py

app.py

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+import numpy as np
+import tensorflow as tf
+from tensorflow import keras
+
+model = tf.keras.models.load_model("Air_Cooler.keras")
+
+def comp(Tempurature,Flowrate):
+    Tempurature = Tempurature/40
+    Flowrate = Flowrate/2120312
+    Xn = np.array([[Tempurature,Flowrate]])
+    Yn = abs(model.predict(Xn))
+    Power = np.round(Yn[0,0]*132.3, 2)
+    Tempurature = np.round(Yn[0,1]*93, 2)
+    return Power, Tempurature
+
+demo = gr.Interface(fn=comp,inputs=["number", "number"],outputs=["number", "number"],
+                   title="Air Cooler Performance Model",
+                    description="This model is built by Deep Nural Network for evaluating performance of Air Cooler used for CO2 cooling. Here, you have to define Atmospheric air temperature in (Deg.C) and Air flowrate in (Kg/hr). First output is Fan Power in (KW) and second output is Cooled CO2 Temperature in (Deg.C)."
+    )
+demo.launch()