Update app.py

app.py

@@ -81,18 +81,14 @@ custom_css = """
 with gr.Blocks(css=custom_css) as interface:
     gr.Markdown(
         """
-# QR Code AI Art Generator
-## 💡 How to generate beautiful QR codes
-We use the QR code image as the initial image **and** the control image, which allows you to generate 
-QR Codes that blend in **very naturally** with your provided prompt.
-The strength parameter defines how much noise is added to your QR code and the noisy QR code is then guided towards both your prompt and the QR code image via Controlnet.
-Use a high strength value between 0.8 and 0.95 and choose a conditioning scale between 0.6 and 2.0.
-This mode arguably achieves the asthetically most appealing QR code images, but also requires more tuning of the controlnet conditioning scale and the strength value. If the generated image 
-looks way to much like the original QR code, make sure to gently increase the *strength* value and reduce the *conditioning* scale. Also check out the examples below.
-model: https://huggingface.co/DionTimmer/controlnet_qrcode-control_v1p_sd15
-<a href="https://huggingface.co/spaces/huggingface-projects/QR-code-AI-art-generator?duplicate=true" style="display: inline-block;margin-top: .5em;margin-right: .25em;" target="_blank">
-<img style="margin-bottom: 0em;display: inline;margin-top: -.25em;" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a> for no queue on your own hardware.</p>
-                """
+# NeuralVista
+##  Welcome to NeuralVista, a powerful tool designed to help you visualize object detection models in action. With the integration of state-of-the-art YOLO models, you can explore the performance of object detection algorithms on various images.
+
+Whether you're looking to analyze pre-existing samples or upload your own images, 
+NeuralVista allows you to experiment with different YOLO versions, providing you with valuable 
+insights into how these models interpret and detect objects. Additionally, 
+you can view deep feature factorization outputs and gain a deeper understanding of model behavior at different layers, 
+all within an intuitive interface."""
     )
     
     # Default sample
@@ -147,11 +143,10 @@ model: https://huggingface.co/DionTimmer/controlnet_qrcode-control_v1p_sd15
     with gr.Row(elem_classes="custom-row"):
         dff_gallery = gr.Gallery(
             label="Deep Feature Factorization",
-            rows=1,
-            columns=1,
+            rows=8,          # 8 rows
+            columns=1,       # 1 image per row
             object_fit="fit",
-            height=150  # Adjust as needed
-
+            height="auto"    # Adjust as needed
         )