Fixed gradio blocks UI code

app.py

@@ -552,45 +552,45 @@ with gr.Blocks() as demo:
                     with TabItem("Display saliency map plot"):
                         det_saliency_plot = Plot()
 
-# Image Classification dropdown list event listeners        
-drop_list.select(select_img_cls_model,drop_list,drop_list)
-drop_list_sal.select(select_img_cls_saliency_algo,drop_list_sal,drop_list_sal)
-drop_list_sal.change(show_textbox_parameters,drop_list_sal,[window_size,stride,masks,spatial_res,seed])
-drop_list_sal.change(show_slider_parameters,drop_list_sal,[threads,p1])
-drop_list_sal.change(show_debiased_checkbox,drop_list_sal,debiased)
-
-# Image Classification textbox, slider and checkbox event listeners   
-window_size.submit(enter_window_size,window_size,window_size)
-masks.submit(enter_num_masks,masks,masks)
-stride.submit(enter_stride, stride, stride)
-spatial_res.submit(enter_spatial_res, spatial_res, spatial_res)
-seed.submit(enter_seed, seed, seed)
-threads.change(select_threads, threads, threads)
-p1.change(select_p1, p1, p1)
-debiased.change(check_debiased,debiased,debiased)
-
-# Image Classification prediction and saliency generation event listeners
-classify.click(predict, [input_img, num_classes], [class_label,class_name])
-class_label.select(map_labels,None,class_name)
-generate_saliency.click(interpretation_function, [input_img, class_label, class_name, img_alpha, sal_alpha, min_sal_range, max_sal_range], [interpretation,interpretation_plot])
-
-# Object Detection dropdown list event listeners
-drop_list_detect_model.select(select_obj_det_model,drop_list_detect_model,drop_list_detect_model)
-drop_list_detect_sal.select(select_obj_det_saliency_algo,drop_list_detect_sal,drop_list_detect_sal)
-drop_list_detect_sal.change(show_slider_parameters,drop_list_detect_sal,[threads_detect,p1_detect])
-drop_list_detect_sal.change(show_textbox_parameters,drop_list_detect_sal,[masks_detect,spatial_res_detect,seed_detect,occlusion_grid_size])
-
-# Object detection textbox and slider event listeners   
-masks_detect.submit(enter_num_masks,masks_detect,masks_detect)
-occlusion_grid_size.submit(enter_occlusion_grid_size,occlusion_grid_size,occlusion_grid_size)
-spatial_res_detect.submit(enter_spatial_res, spatial_res_detect, spatial_res_detect)
-seed_detect.submit(enter_seed, seed_detect, seed_detect)
-threads_detect.change(select_threads, threads_detect, threads_detect)
-p1_detect.change(select_p1, p1_detect, p1_detect)
-
-# Object detection prediction, class selection and saliency generation event listeners
-detection.click(run_detect, [input_img_detect, num_detections], [detect_label,class_name_det])
-detect_label.select(map_labels, None, class_name_det)
-generate_det_saliency.click(run_detect_saliency,[input_img_detect, num_detections, class_name_det, img_alpha_det, sal_alpha_det, min_sal_range_det, max_sal_range_det],det_saliency_plot)
+    # Image Classification dropdown list event listeners        
+    drop_list.select(select_img_cls_model,drop_list,drop_list)
+    drop_list_sal.select(select_img_cls_saliency_algo,drop_list_sal,drop_list_sal)
+    drop_list_sal.change(show_textbox_parameters,drop_list_sal,[window_size,stride,masks,spatial_res,seed])
+    drop_list_sal.change(show_slider_parameters,drop_list_sal,[threads,p1])
+    drop_list_sal.change(show_debiased_checkbox,drop_list_sal,debiased)
+
+    # Image Classification textbox, slider and checkbox event listeners   
+    window_size.submit(enter_window_size,window_size,window_size)
+    masks.submit(enter_num_masks,masks,masks)
+    stride.submit(enter_stride, stride, stride)
+    spatial_res.submit(enter_spatial_res, spatial_res, spatial_res)
+    seed.submit(enter_seed, seed, seed)
+    threads.change(select_threads, threads, threads)
+    p1.change(select_p1, p1, p1)
+    debiased.change(check_debiased,debiased,debiased)
+
+    # Image Classification prediction and saliency generation event listeners
+    classify.click(predict, [input_img, num_classes], [class_label,class_name])
+    class_label.select(map_labels,None,class_name)
+    generate_saliency.click(interpretation_function, [input_img, class_label, class_name, img_alpha, sal_alpha, min_sal_range, max_sal_range], [interpretation,interpretation_plot])
+
+    # Object Detection dropdown list event listeners
+    drop_list_detect_model.select(select_obj_det_model,drop_list_detect_model,drop_list_detect_model)
+    drop_list_detect_sal.select(select_obj_det_saliency_algo,drop_list_detect_sal,drop_list_detect_sal)
+    drop_list_detect_sal.change(show_slider_parameters,drop_list_detect_sal,[threads_detect,p1_detect])
+    drop_list_detect_sal.change(show_textbox_parameters,drop_list_detect_sal,[masks_detect,spatial_res_detect,seed_detect,occlusion_grid_size])
+
+    # Object detection textbox and slider event listeners   
+    masks_detect.submit(enter_num_masks,masks_detect,masks_detect)
+    occlusion_grid_size.submit(enter_occlusion_grid_size,occlusion_grid_size,occlusion_grid_size)
+    spatial_res_detect.submit(enter_spatial_res, spatial_res_detect, spatial_res_detect)
+    seed_detect.submit(enter_seed, seed_detect, seed_detect)
+    threads_detect.change(select_threads, threads_detect, threads_detect)
+    p1_detect.change(select_p1, p1_detect, p1_detect)
+
+    # Object detection prediction, class selection and saliency generation event listeners
+    detection.click(run_detect, [input_img_detect, num_detections], [detect_label,class_name_det])
+    detect_label.select(map_labels, None, class_name_det)
+    generate_det_saliency.click(run_detect_saliency,[input_img_detect, num_detections, class_name_det, img_alpha_det, sal_alpha_det, min_sal_range_det, max_sal_range_det],det_saliency_plot)
 
 demo.launch()