merge

.idea/workspace.xml

@@ -0,0 +1,192 @@
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app.py

@@ -16,7 +16,7 @@ from factories import PhysicsWithGenerator, EvalModel, BaselineModel, EvalDatase
 
 
 ### Config
-DEVICE_STR = 'cuda'            # run model inference on NVIDIA gpu
+DEVICE_STR = 'cuda' if torch.cuda.is_available() else 'cpu'            # run model inference on NVIDIA gpu
 torch.set_grad_enabled(False)  # stops tracking values for gradients
 
 
@@ -164,10 +164,10 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
     ### LAYOUT
     # Display images
     with gr.Row():
-        gt_img = gr.Image(label="Ground-truth IMAGE", interactive=True)
-        observed_img = gr.Image(label="Observed IMAGE", interactive=False)
-        model_a_out = gr.Image(label="RAM OUTPUT", interactive=False)
-        model_b_out = gr.Image(label="DPIR OUTPUT", interactive=False)
+        gt_img = gr.Image(label="Ground-truth image", interactive=True)
+        observed_img = gr.Image(label="Observed image", interactive=False)
+        model_a_out = gr.Image(label="RAM output", interactive=False)
+        model_b_out = gr.Image(label="DPIR output", interactive=False)
 
     @gr.render(inputs=[dataset_placeholder, physics_placeholder, available_physics_placeholder])
     def dynamic_layout(dataset, physics, available_physics):
@@ -175,23 +175,23 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
 
         # Manage datasets and display metric values
         with gr.Row():
-            with gr.Column():
-                run_button = gr.Button("Demo on above image")
+            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=0)
                 with gr.Row():
-                    load_button = gr.Button("Run on index image from dataset")
-                    load_random_button = gr.Button("Run on random image from dataset")
-            with gr.Column():
-                observed_metrics = gr.Textbox(label="PSNR(Observed, Ground-truth)",
+                    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="PSNR Observed",
                                               lines=1)
-            with gr.Column():
-                out_a_metric = gr.Textbox(label="PSNR(RAM, Ground-truth)",
+            with gr.Column(scale=1, min_width=160):
+                out_a_metric = gr.Textbox(label="PSNR RAM output",
                                           lines=1)
-            with gr.Column():
-                out_b_metric = gr.Textbox(label="PSNR(DPIR, Ground-truth)",
+            with gr.Column(scale=1, min_width=160):
+                out_b_metric = gr.Textbox(label="PSNR DPIR",
                                           lines=1)
 
         # Manage physics
@@ -200,7 +200,7 @@ with gr.Blocks(title=title, theme=gr.themes.Glass()) as interface:
                 choose_physics = gr.Radio(choices=available_physics,
                                           label="Physics",
                                           value=physics.name)
-                use_generator_button = gr.Checkbox(label="Generate physics parameters during inference")
+                use_generator_button = gr.Checkbox(label="Generate physics parameters during inference", value=True)
             with gr.Column(scale=1):
                 with gr.Row():
                     key_selector = gr.Dropdown(choices=list(physics.saved_params["updatable_params"].keys()),