updates (#2)

- renamed files (bb23732740b4201ba2107391aedec10222986b3c)
- small description fixes (89d2adac6a61df1946d24dba085a322d268a21da)


Co-authored-by: Nikita Karaev <nikkar@users.noreply.huggingface.co>

app.py

@@ -192,7 +192,7 @@ british_museum_images = glob.glob(f'vggsfm_code/examples/british_museum/images/*
 
 
 with gr.Blocks() as demo:
-    gr.Markdown("# 🎨 VGGSfM: Visual Geometry Grounded Deep Structure From Motion")
+    gr.Markdown("# 🏛️ VGGSfM: Visual Geometry Grounded Deep Structure From Motion")
     
     gr.Markdown("""
     <div style="text-align: left;"> 
@@ -200,7 +200,7 @@ with gr.Blocks() as demo:
     This space demonstrates 3D reconstruction from input image frames. </p> 
     <p>To get started quickly, you can click on our <strong> examples (the bottom of the page) </strong>. If you want to reconstruct your own data, simply: </p> 
     <ul style="display: inline-block; text-align: left;"> 
-        <li>upload the images (.jpg, .png, etc.), or </li> 
+        <li>upload images (.jpg, .png, etc.), or </li> 
         <li>upload a video (.mp4, .mov, etc.) </li> 
     </ul> 
     <p>If both images and videos are uploaded, the demo will only reconstruct the uploaded images. By default, we extract <strong> 1 image frame per second from the input video </strong>. To prevent crashes on the Hugging Face space, we currently limit reconstruction to the first 25 image frames. </p>