wtf

app.py

@@ -11,6 +11,8 @@ from point_e.diffusion.configs import DIFFUSION_CONFIGS, diffusion_from_config
 from point_e.diffusion.sampler import PointCloudSampler
 from point_e.models.download import load_checkpoint
 from point_e.models.configs import MODEL_CONFIGS, model_from_config
+from point_e.util.plotting import plot_point_cloud
+from point_e.util.ply_util import write_ply
 
 from diffusers import StableDiffusionPipeline
 
@@ -117,7 +119,7 @@ def generate_3D(input, model_name='base1B', guidance_scale=3.0, grid_size=128):
     set_state('Converting to mesh...')
 
     uniqid = uuid.uuid4()
-    file_path = f'/tmp/mesh-{uniqid}.npy'
+    file_path = f'/tmp/mesh-{uniqid}.ply'
     save_ply(pc, file_path)
 
     set_state('')
@@ -148,10 +150,10 @@ def ply_to_glb(ply_file, glb_file):
 
     return glb_file
 
-def save_plz(pc, file_name):
+def save_ply(pc, file_name):
     # Produce a mesh (with vertex colors)
     with open(file_name, 'wb') as f:
-        np.save(f, pc.coords)
+        pc.write_ply(f)
 
 
 def create_gif(pc):
@@ -219,6 +221,7 @@ with block:
                 Based on the <a href="https://github.com/openai/point-e">Point-E</a> implementation
                 </p>
                 <br />
+                <p>There's only one step left before you can train your model: <a href="https://huggingface.co/spaces/{os.environ['SPACE_ID']}/settings" style="text-decoration: underline" target="_blank">attribute a <b>T4 GPU</b> to it (via the Settings tab)</a> and run the training below. Other GPUs are not compatible for now. You will be billed by the minute from when you activate the GPU until when it is turned it off.</p>
                 </div>
             ''')
         else: