Tweaking demo to outline download times

demo.py

@@ -25,11 +25,11 @@ import utils.export as export
 
 def get_reconstructed_scene(outdir, model, device, silent, image_size, ios_mode, filelist):
 
+ assert len(filelist) == 2, "Please provide two images"
  if ios_mode:
  filelist = [f[0] for f in filelist]
  if len(filelist) == 1:
  filelist = [filelist[0], filelist[0]]
- assert len(filelist) == 2, "Please provide two images"
  imgs = load_images(filelist, size=image_size, verbose=not silent)
 
  for img in imgs:
@@ -110,9 +110,10 @@ if __name__ == '__main__':
  gradio.Markdown('''
  ## Output
  Below we show the generated 3D Gaussian Splat.
- There may be a short delay as the reconstruction needs to be downloaded before rendering.
+ The generated splats are 30-40MB, so please allow up to 30 seconds for them to be downloaded from Hugging Face before rendering.
+ In the mean time your previous generations may be visible.
  The arrow in the top right of the window below can be used to download the .ply for rendering with other viewers,
- such as [here](https://projects.markkellogg.org/threejs/demo_gaussian_splats_3d.php?art=1&cu=0,-1,0&cp=0,1,0&cla=1,0,0&aa=false&2d=false&sh=0) or [here](https://playcanvas.com/supersplat/editor)
+ such as [here](https://projects.markkellogg.org/threejs/demo_gaussian_splats_3d.php?art=1&cu=0,-1,0&cp=0,1,0&cla=1,0,0&aa=false&2d=false&sh=0) or [here](https://playcanvas.com/supersplat/editor).
  ''')
  outmodel = gradio.Model3D(
  clear_color=[1.0, 1.0, 1.0, 0.0],
@@ -122,6 +123,8 @@ if __name__ == '__main__':
  gradio.Markdown('''
  ## Examples
  A gallery of examples generated from ScanNet++ and from 'in the wild' images taken with a mobile phone.
+ These examples are 30-40MB, so please allow up to 30 seconds for them to be downloaded from Hugging Face before rendering.
+ In the mean time your previous generations may be visible.
  ''')
  
  snapshot_1 = gradio.Image(None, visible=False)