Update api.py

api.py

@@ -135,7 +135,7 @@ loaded_scaler = joblib.load('scaler.joblib')
 # Load the saved label encoder
 loaded_label_encoder = joblib.load('label_encoder.joblib')
 
-model = tf.keras.models.load_model('keras_model.h5')
+Geomodel = tf.keras.models.load_model('keras_model.h5')
 
 
 
@@ -186,7 +186,7 @@ def predict_crop_disease(input_data):
 
     print(input_scaled.reshape(1,-1).shape)
     # Make predictions
-    prediction = model.predict(input_scaled)
+    prediction = Geomodel.predict(input_scaled)
 
     # Inverse transform the prediction (if needed, depending on your model)
     #predicted_label = loaded_label_encoder.inverse_transform(prediction)