update interface

app.py

@@ -28,7 +28,7 @@ def resize_tensor_within_box(tensor_img: torch.Tensor, max_size: int = 512):
     return tensor_img
 
 def generate_imgs_from_user(image,
-                            physics: PhysicsWithGenerator, use_gen: bool,
+                            physics: PhysicsWithGenerator, # use_gen: bool,
                             baseline: BaselineModel, model: EvalModel,
                             metrics: List[Metric]):
     # Happens when user image is missing
@@ -242,13 +242,10 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
         with gr.Row():
             with gr.Column(scale=1, min_width=160):
                 run_button = gr.Button("Demo on above image", size='md')
-                choose_dataset = gr.Radio(choices=EvalDataset.all_datasets,
-                                          label="Datasets",
-                                          value=dataset.name)
-                idx_slider = gr.Slider(minimum=0, maximum=len(dataset)-1, step=1, label="Sample index", key='idx_slider')
                 with gr.Row():
                     load_button = gr.Button("Run on index image from dataset", size='md')
                     load_random_button = gr.Button("Run on random image from dataset", size='md')
+
             with gr.Column(scale=1, min_width=160):
                 observed_metrics = gr.Textbox(label="Observed metric", lines=2, key='metrics')
             with gr.Column(scale=1, min_width=160):
@@ -256,13 +253,16 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
             with gr.Column(scale=1, min_width=160):
                 out_b_metric = gr.Textbox(label="DPIR output metrics", lines=2, key='dpir_metrics')
 
-        # Manage physics
         with gr.Row():
             with gr.Column(scale=1):
                 choose_physics = gr.Radio(choices=available_physics,
                                           label="Physics",
                                           value=physics.name)
-                use_generator_button = gr.Checkbox(label="Generate physics parameters during inference", value=True, key='use_gen')
+                choose_dataset = gr.Radio(choices=EvalDataset.all_datasets,
+                                          label="Datasets",
+                                          value=dataset.name)
+                idx_slider = gr.Slider(minimum=0, maximum=len(dataset) - 1, step=1, label="Sample index",
+                                       key='idx_slider')
             with gr.Column(scale=1):
                 with gr.Row():
                     key_selector = gr.Dropdown(choices=list(physics.saved_params["updatable_params"].keys()),
@@ -272,7 +272,7 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
             with gr.Column(scale=2):
                 physics_params = gr.Textbox(label="Physics parameters",
                                             lines=5,
-                                            value=physics.display_saved_params())  
+                                            value=physics.display_saved_params())
 
         ### Event listeners
 
@@ -287,7 +287,7 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
         run_button.click(fn=generate_imgs_from_user_partial,
                          inputs=[gt_img,
                                  physics_placeholder,
-                                 use_generator_button,
+                                 # use_generator_button,
                                  model_b_placeholder],
                          outputs=[gt_img, observed_img, model_a_out, model_b_out,
                                   physics_params, observed_metrics, out_a_metric, out_b_metric])
@@ -295,14 +295,14 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
                           inputs=[dataset_placeholder,
                                   idx_slider,
                                   physics_placeholder,
-                                  use_generator_button,
+                                  # use_generator_button,
                                   model_b_placeholder],
                           outputs=[gt_img, observed_img, model_a_out, model_b_out,
                                    physics_params, observed_metrics, out_a_metric, out_b_metric])
         load_random_button.click(fn=generate_random_imgs_from_dataset_partial,
                                  inputs=[dataset_placeholder,
                                          physics_placeholder,
-                                         use_generator_button,
+                                         # use_generator_button,
                                          model_b_placeholder],
                                  outputs=[idx_slider, gt_img, observed_img, model_a_out, model_b_out,
                                           physics_params, observed_metrics, out_a_metric, out_b_metric])