Update app.py

app.py

@@ -146,12 +146,13 @@ def predict_deep_learning(model_name, file):
             plt.imshow(img_data, cmap='gray', alpha=0.5)
             plt.imshow(overlay, cmap='jet', alpha=0.5)
             plt.title('Crop Yield Prediction Overlay')
-            # plt.colorbar()
             plt.savefig('/tmp/dl_prediction_overlay.png')
 
             return '/tmp/dl_prediction_overlay.png'
         else:
             return "No file uploaded"
+    elif model_name == 'Random Forest':
+        return predict_random_forest(file)
     else:
         return "Model not found"
 
@@ -181,7 +182,7 @@ with gr.Blocks() as demo:
         
     with gr.Tab("Deep Learning Models"):
         gr.Interface(
-            fn=lambda model_name, file: predict_deep_learning(model_name, file) if model_name != 'Random Forest' else predict_random_forest(file),
+            fn=predict_deep_learning,
             inputs=inputs_deep_learning,
             outputs=outputs_deep_learning,
             title="Crop Yield Prediction using Deep Learning Models and Random Forest"