Update app.py

app.py

@@ -48,7 +48,7 @@ def normalize_point_clouds(pcs,mode):
     
 
 
-def predict(Seed,ckpt,truncate_std):
+def predict(Seed,ckpt):
   if Seed==None:
     Seed=777 
   seed_all(Seed)
@@ -63,14 +63,14 @@ def predict(Seed,ckpt,truncate_std):
   gen_pcs = []
   with torch.no_grad():
       z = torch.randn([1, ckpt['args'].latent_dim]).to(device)
-      x = model.sample(z, 2048, flexibility=ckpt['args'].flexibility,truncate_std=truncate_std)
+      x = model.sample(z, 2048, flexibility=ckpt['args'].flexibility)
       gen_pcs.append(x.detach().cpu())
   gen_pcs = torch.cat(gen_pcs, dim=0)[:1]
   gen_pcs = normalize_point_clouds(gen_pcs, mode="shape_bbox")
 
   return gen_pcs[0]
 
-def generate(seed,value,truncate_std):
+def generate(seed,value):
     if value=="Airplane":
       ckpt=ckpt_airplane
     elif value=="Chair":
@@ -79,7 +79,7 @@ def generate(seed,value,truncate_std):
        ckpt=ckpt_airplane
 
     colors=(238, 75, 43)
-    points=predict(seed,ckpt,truncate_std)
+    points=predict(seed,ckpt)
     num_points=points.shape[0]
 
 
@@ -126,11 +126,11 @@ with gr.Blocks() as demo:
         with gr.Row():
             seed = gr.Slider( minimum=0, maximum=2**16,label='Seed')
             value=gr.Dropdown(choices=["Airplane","Chair"],label="Choose Model Type")
-            truncate_std = gr.Slider( minimum=1, maximum=2,label='Truncate Std')
+            #truncate_std = gr.Slider( minimum=1, maximum=2,label='Truncate Std')
 
         btn = gr.Button(value="Generate")
         point_cloud = gr.Plot()
-    demo.load(generate, [seed,value,truncate_std], point_cloud)
-    btn.click(generate, [seed,value,truncate_std], point_cloud)
+    demo.load(generate, [seed,value], point_cloud)
+    btn.click(generate, [seed,value], point_cloud)
 
 demo.launch()