better display

app.py

@@ -32,7 +32,6 @@ from inference import (
     infer_image,
 )
 
-
 # ---------------------------------------------------------------------------
 # Configuration
 # ---------------------------------------------------------------------------
@@ -404,12 +403,12 @@ def load_dataset_sample(
 
         target = meta.get("target")
         # Generate ground truth display
-        ground_truth_update = gr.update(visible=False)
+        ground_truth_update = gr.update(value="")
         if target is not None:
             # Use id_to_labels.json mapping
             id2label = load_id_to_labels().get(head, {})
             label_name = id2label.get(target, str(target))
-            ground_truth_update = gr.update(value=f"**Ground Truth:** {label_name} (class {target})", visible=True)
+            ground_truth_update = gr.update(value=f"{label_name} (class {target})", visible=True)
 
         return (
             display,
@@ -448,7 +447,7 @@ def run_inference(
         output = infer_image(image, head, image_state.get("mask"), return_probs=head not in REGRESSION_HEADS)
 
         if head in REGRESSION_HEADS:
-            return f"**Prediction:** {output:.3f}", gr.update(visible=False)
+            return f"{output:.3f}", gr.update(visible=False)
 
         # Use id_to_labels.json mapping, fall back to model config if not available
         id2label = load_id_to_labels().get(head, {})
@@ -456,13 +455,12 @@ def run_inference(
         df = format_probabilities(output, id2label)
         top_row = df.iloc[0]
         prediction = f"{top_row['label']} (p={top_row['probability']:.3f})"
-        result_text = f"**Prediction:** {prediction}"
+        result_text = prediction
         return result_text, gr.update(visible=True, value=df)
     except Exception as exc:  # pragma: no cover - surfaced in UI
         traceback.print_exc()
         return f"Failed to run inference: {exc}", gr.update(visible=False)
 
-
 def handle_upload_preview(
     image: np.ndarray | Image.Image | None,
     head: str,
@@ -485,11 +483,11 @@ def handle_upload_preview(
             "Image uploaded. Click 'Run inference' to compute predictions.",
             "",  # Reset prediction text
             pd.DataFrame(),
-            gr.update(visible=False),
+            gr.update(value=""),
             {"image": np_image, "mask": None},  # Store raw image for inference
         )
     except Exception as exc:  # pragma: no cover - surfaced in UI
-        return None, f"Failed to load image: {exc}", "", pd.DataFrame(), gr.update(visible=False), None
+        return None, f"Failed to load image: {exc}", "", pd.DataFrame(),  gr.update(value=""), None
 
 
 # ---------------------------------------------------------------------------
@@ -518,11 +516,11 @@ def build_demo() -> gr.Blocks:
             value=default_head,
         )
 
-        gr.Markdown("---")
+        # gr.Markdown("---")
 
         with gr.Row():
             with gr.Column():
-                gr.Markdown("### Load dataset sample")
+                # gr.Markdown("### Load dataset sample")
                 dataset_display = gr.Markdown(f"**Dataset:** {DATASET_OPTIONS.get(DEFAULT_DATASET_FOR_HEAD.get(default_head, ''), 'Unknown')}")
                 dataset_status = gr.Markdown("Select a model head to load class metadata.")
                 class_dropdown = gr.Dropdown(label="Target class filter", choices=["Random"], value="Random")
@@ -556,9 +554,8 @@ def build_demo() -> gr.Blocks:
                 image_display = gr.Image(label="Image", interactive=False, type="numpy")
 
             with gr.Column():
-                ground_truth_display = gr.Markdown(visible=False)
-                gr.Markdown("### Predictions")
-                main_prediction = gr.Markdown()
+                ground_truth_display = gr.Textbox(label="Ground Truth", interactive=False)
+                main_prediction = gr.Textbox(label="Prediction", value="", interactive=False)
                 prediction_probs = gr.Dataframe(headers=["class_id", "label", "probability"], visible=False)
 
         image_state = gr.State()