Rename mask UI to field; fix sigma at 0.2

app.py

@@ -625,7 +625,7 @@ def apply_example(example):
         mcx,
         mcy,
         example.get("mask_radius", 0.3),
-        example.get("mask_sigma", 0.2),
+        0.2,  # fixed field sigma (fall-off); not exposed in simple UI
         example.get("eps_max_mult", 4.0),
         example.get("eps_min_mult", 1.0),
         example.get("step_max_mult", 4.0),
@@ -664,13 +664,13 @@ with gr.Blocks(title="Human Hallucination Prediction", css="""
             # Inputs (track path so save filenames use stimulus name when from example)
             default_image_path = os.path.join("stimuli", "urbanoffice1.jpg")
             image_input = gr.Image(
-                label="Input Image (click to set mask center)",
+                label="Input Image (click to set field center)",
                 type="pil",
                 value=_image_to_pil(default_image_path),
             )
             current_image_path_state = gr.State(value=default_image_path)
             mask_preview = gr.Image(
-                label="Mask center preview (click to set center — circle shows mask)",
+                label="Field center preview (click to set center — circle shows field)",
                 type="pil",
                 interactive=False,
             )
@@ -705,13 +705,13 @@ with gr.Blocks(title="Human Hallucination Prediction", css="""
                 
                 with gr.Row():
                     use_adaptive_eps_check = gr.State(value=False)
-                    use_adaptive_step_check = gr.Checkbox(value=True, label="Use adaptive step size (stronger/weaker updates by region)")
+                    use_adaptive_step_check = gr.Checkbox(value=True, label="Use adaptive step size (stronger/weaker updates by field)")
                 with gr.Row():
-                    mask_center_x_slider = gr.Slider(minimum=-1.0, maximum=1.0, value=0.5, step=0.05, label="Mask center X")
-                    mask_center_y_slider = gr.Slider(minimum=-1.0, maximum=1.0, value=0.0, step=0.05, label="Mask center Y")
+                    mask_center_x_slider = gr.Slider(minimum=-1.0, maximum=1.0, value=0.5, step=0.05, label="Field center X")
+                    mask_center_y_slider = gr.Slider(minimum=-1.0, maximum=1.0, value=0.0, step=0.05, label="Field center Y")
                 with gr.Row():
-                    mask_radius_slider = gr.Slider(minimum=0.01, maximum=1.0, value=0.2, step=0.01, label="Mask radius (flat region size)")
-                    mask_sigma_slider = gr.Slider(minimum=0.05, maximum=1.0, value=0.2, step=0.01, label="Mask sigma (fall-off outside radius)")
+                    mask_radius_slider = gr.Slider(minimum=0.01, maximum=1.0, value=0.2, step=0.01, label="Field radius")
+                mask_sigma_slider = gr.State(value=0.2)
                 eps_max_mult_slider = gr.State(value=1.0)
                 eps_min_mult_slider = gr.State(value=1.0)
                 with gr.Row():
@@ -810,7 +810,7 @@ with gr.Blocks(title="Human Hallucination Prediction", css="""
         outputs=[params_section],
     )
 
-    # Click on input image or mask preview to set Gaussian mask center
+    # Click on input image or field preview to set Gaussian field center
     def _mask_preview_inputs():
         return [image_input, mask_center_x_slider, mask_center_y_slider, mask_radius_slider]