diff --git a/Cellpose_gradio.py b/Cellpose_gradio.py
index 2adf9a9..398d48b 100644
--- a/Cellpose_gradio.py
+++ b/Cellpose_gradio.py
@@ -1,12 +1,13 @@
 import gradio as gr
 import numpy as np
-import os
-from cellpose import models, utils
 import matplotlib.pyplot as plt
+from cellpose import models, utils
 from PIL import Image
 from datetime import datetime
-import json
 from werkzeug.utils import secure_filename
+import json
+import os
+import io
 
 ########################################################
 # 1. Utility functions
@@ -121,7 +122,7 @@ def save_masks(image, masks):
         overlay = utils.masks_to_outlines(masks)
         Image.fromarray(overlay).save(outlines_filename)
         outlines_path = os.path.abspath(outlines_filename)
-
+        
         return [npy_path, png_path, outlines_path]
     return None
 
@@ -227,6 +228,8 @@ def process_and_display(image, model_type, diameter, flow_threshold, display_cha
     3. Generates a figure displaying the segmentation results.
     4. Counts the number of cells in the segmented image.
     5. Saves the segmentation masks to files.
+    6. Saves a high-quality version of the plot as a PNG file.
+    7. Saves the plot as an SVG file.
 
     Args:
         image (numpy.ndarray): Input image for segmentation.
@@ -242,8 +245,9 @@ def process_and_display(image, model_type, diameter, flow_threshold, display_cha
     Returns:
         tuple: Contains the following elements:
             - fig (matplotlib.figure.Figure): Figure object with segmentation results.
-            - mask_files (list): Paths to saved mask files.
+            - mask_files (list): Paths to saved mask files and high-quality plot.
             - cell_count (int): Number of cells detected.
+            - settings_summary (str): Summary of the settings used for segmentation.
             - gr.update: Gradio update object to hide/show error alerts.
     """
     try:
@@ -261,22 +265,51 @@ def process_and_display(image, model_type, diameter, flow_threshold, display_cha
             progress(0.1, desc="Segmentation starting...")
             channels = [seg_channel1, seg_channel2]
             
+            # Segment the image
             progress(0.25, desc="Segmentation in progress...")
             masks = segment_image(image, model_type, channels=channels, diameter=diameter, flow_threshold=flow_threshold)
             progress(0.75, desc="Segmentation complete. Generating results...")
             
+            # Display the results
             fig = display_results(image, masks, display_channel=display_channel, cmap=cmap)
             cell_count = count_cells(masks)
             mask_files = save_masks(image, masks)
             
+            # Save the figure as a high-quality PNG
+            buf = io.BytesIO()
+            fig.savefig(buf, format='png', dpi=300, bbox_inches='tight')
+            buf.seek(0)
+
+            # Save the plot to a file.png
+            plot_filename = os.path.join("Outputs", f"Result_figure_{datetime.now().strftime('%Y%m%d_%H%M%S')}.png")
+            with open(plot_filename, 'wb') as f:
+                f.write(buf.getvalue())
+            
+            # Add the PNG plot to mask_files
+            mask_files.append(plot_filename)
+
+            # Save the figure as an SVG
+            svg_buf = io.BytesIO()
+            fig.savefig(svg_buf, format='svg', bbox_inches='tight')
+            svg_buf.seek(0)
+
+            # Save the plot as an SVG
+            svg_filename = os.path.join("Outputs", f"Result_figure_{datetime.now().strftime('%Y%m%d_%H%M%S')}.svg")
+            with open(svg_filename, 'wb') as f:
+                f.write(svg_buf.getvalue())
+
+            # Add the SVG plot to mask_files
+            mask_files.append(svg_filename)
+            
             progress(1.0, desc="Process complete!")
-            return fig, mask_files, cell_count, gr.update(visible=False)
+            settings_summary = f"Model: {model_type}, Diameter: {diameter}, Flow Threshold: {flow_threshold}, Display: {display_channel}, Seg Ch1: {seg_channel1}, Seg Ch2: {seg_channel2}, Colormap: {cmap}"
+            return fig, mask_files, cell_count, settings_summary, gr.update(visible=False)
         gr.Error("No image provided.")
-        return None, None, None, gr.update(visible=True)
+        return None, None, None, None, gr.update(visible=True)
     
     except Exception as e:
-        gr.Error(str(e))  # Show error message
-        return None, None, None, gr.update(visible=True)
+        gr.Error(str(e))
+        return None, None, None, None, gr.update(visible=True)
 
 def update_channel_visibility(channel_config):
     """
@@ -456,6 +489,18 @@ def load_settings(profile_name):
     background-color: #fdedd6;
     color: white;
 }
+.custom-settings-summary {
+    font-weight: bold;
+    font-size: 10px;
+}
+.custom-settings-summary textarea {
+    font-weight: bold !important;
+    font-size: 10px !important;
+}
+.custom-settings-summary:hover {
+    background-color: #fdedd6;
+    color: white;
+}
 """
 
 custom_theme = gr.themes.Soft(primary_hue="orange", secondary_hue="orange", font=["Arial", "sans-serif"])
@@ -482,7 +527,9 @@ def load_settings(profile_name):
             profile_name = gr.Textbox(label="Save Profile", placeholder="Enter profile name", info="Name your profile to **save the current settings**.", elem_classes=["custom-component"])
             save_btn = gr.Button("Save Profile", scale=1, size="sm", elem_classes=["custom-button"])
         with gr.Column(scale=1):
-            load_profile = gr.Dropdown(label="Load Profile", choices=list_profiles(), scale=1, info="Select a profile to **load its settings**.", elem_classes=["custom-dropdown"])
+            profiles = list_profiles()
+            default_value = profiles[0] if profiles else None
+            load_profile = gr.Dropdown(label="Load Profile", choices=profiles, scale=1, info="Select a profile to **load its settings**.", value=default_value, allow_custom_value=True, elem_classes=["custom-dropdown"])
             load_btn = gr.Button("Load Profile", scale=1, size="sm", elem_classes=["custom-button"])    
     
     # Model type, diameter, flow threshold
@@ -527,26 +574,31 @@ def load_settings(profile_name):
                 )
     
     process_btn = gr.Button("Run Segmentation", scale=2, elem_classes=["custom-button"])
-
-    # Output plot + progress animation
-    with gr.Row():
-        output_plot = gr.Plot(label="Segmentation Results")
-        progress_output = gr.Textbox(label="Progress", interactive=False, visible=False)
-    
-    # Output files and cell count
-    with gr.Row():
-        cell_count_output = gr.Number(label="Number of cells detected", scale=1, elem_classes=["custom-component"])
-        output_files = gr.File(label="Download Results (date and time is in the filename)", file_count="multiple", scale=1, elem_classes=["custom-component"])
-    
-    # buttons logic
+    progress_output = gr.Textbox(label="Progress", interactive=False, visible=True)
     
+    # Output components (initially hidden)
+    with gr.Row(visible=False) as output_row:
+        output_plot = gr.Plot(label="Segmentation Results")
+        
+    with gr.Row(visible=False) as results_row:
+        with gr.Column(scale=1):
+            cell_count_output = gr.Number(label="Number of cells detected", elem_classes=["custom-component"])
+            settings_output = gr.Textbox(label="Settings Summary", elem_classes=["custom-settings-summary"])
+        with gr.Column(scale=2):
+            output_files = gr.File(label="Download Results", file_count="multiple", scale=1, height=500, elem_classes=["custom-component"])
+
+    # Update the process_and_display_wrapper function
+    def process_and_display_wrapper(*args):
+        results = process_and_display(*args)
+        return [gr.update(visible=True), gr.update(visible=True)] + list(results)
+
     # Run segmentation button
     process_btn.click(
-        fn=process_and_display,
+        fn=process_and_display_wrapper,
         inputs=[input_image, model_type, diameter, flow_threshold, display_channel, seg_channel1, seg_channel2, cmap],
-        outputs=[output_plot, output_files, cell_count_output, progress_output]
+        outputs=[output_row, results_row, output_plot, output_files, cell_count_output, settings_output, progress_output],
     )
-    
+
     # Save settings button
     save_btn.click(
         save_settings,