new

app.py

@@ -151,7 +151,7 @@ def text_to_detailed(prompt, seed=None):
 
 @spaces.GPU(duration=120)
 def text_to_image(prompt, seed=None, strength=1.0,lora_scale=1.0, num_inference_steps=20, redux_hparam=None, init_image=None, **kwargs):
-    subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
+    # subprocess.run("rm -rf /data-nvme/zerogpu-offload/*", env={}, shell=True)
     # print(f"Before text_to_image: {torch.cuda.memory_allocated() / 1024**3} GB")
     k3d_wrapper.renew_uuid()
     init_image = None
@@ -237,12 +237,6 @@ def bundle_image_to_mesh(
     
     if if_video:
         video_path = recon_mesh_path.replace('.obj','.mp4').replace('.glb','.mp4')
-        # # 检查这个video_path文件大小是是否超过50KB，不超过的话就认为是空文件，需要重新渲染
-        # if os.path.exists(video_path):
-        #     print(f"file size:{os.path.getsize(video_path)}")
-        #     if os.path.getsize(video_path) > 50*1024:
-        #         print(f"video path:{video_path}")
-        #         return video_path
         render_video_from_obj(recon_mesh_path, video_path)
         print(f"After bundle_image_to_mesh: {torch.cuda.memory_allocated() / 1024**3} GB")
         return video_path