Upload app.py

app.py

@@ -36,7 +36,7 @@ def load_nifti(file):
     mid_index = vol.shape[0] // 2
     slice_img = Image.fromarray((coronal_slices[mid_index] / np.max(coronal_slices[mid_index]) * 255).astype(np.uint8))
     gallery_images = load_gallery_images()
-    return slice_img, gr.update(visible=True, maximum=len(coronal_slices)-1, value=mid_index), gallery_images, gr.update(visible=True), gr.update(visible=False)
+    return slice_img, gr.update(visible=True, maximum=len(coronal_slices)-1, value=mid_index), gallery_images, gr.update(visible=True), gr.update(visible=True)
 
 def update_slice(index):
     if not coronal_slices:
@@ -53,8 +53,7 @@ def update_slice(index):
         new_probs = np.clip(np.array(last_probabilities) + noise, 0, None)
         new_probs /= new_probs.sum()
     else:
-        new_probs = generate_random_probabilities()
-
+        new_probs = []
     return slice_img, plot_probabilities(new_probs), gallery_selection
 
 def load_gallery_images():
@@ -115,7 +114,7 @@ with gr.Blocks() as demo:
 
     with gr.Column(visible=False) as plot_row:
         gr.Markdown("### Step 5: Quantitative results of the mapping model.")
-        prob_plot = gr.BarPlot(prob_df, x="labels", y="values", title="Cell Type Probabilities", scroll_to_output=True, x_label_angle=-90, height = 600)
+        prob_plot = gr.BarPlot(prob_df, x="labels", y="values", title="Cell Type Probabilities", scroll_to_output=True, x_label_angle=-90, height = 400)
         gr.Markdown("### Step 6: Download Results.")
         download_button = gr.DownloadButton(label="Download Results", value='./Cell_types_predictions.csv')