test

app.py

@@ -1,5 +1,7 @@
 import os
 import subprocess
+from setuptools import setup, find_packages
+from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CppExtension
 
 import matplotlib.pyplot as plt
 import torch
@@ -87,11 +89,29 @@ model_option = gr.Radio(options, value="dino16",
                         label='Choose a backbone to upsample')
 
 
-@spaces.GPU(120)
+@spaces.GPU(duration=120)
 def upsample_features(image, model_option):
     with torch.no_grad():
-        subprocess.check_call(
-            ["pip", "install", "git+https://github.com/mhamilton723/FeatUp"])
+        setup(
+            name='featup',
+            version='0.1.2',
+            packages=find_packages(),
+            ext_modules=[
+                CUDAExtension(
+                    'adaptive_conv_cuda_impl',
+                    [
+                        'featup/adaptive_conv_cuda/adaptive_conv_cuda.cpp',
+                        'featup/adaptive_conv_cuda/adaptive_conv_kernel.cu',
+                    ]),
+                CppExtension(
+                    'adaptive_conv_cpp_impl',
+                    ['featup/adaptive_conv_cuda/adaptive_conv.cpp'],
+                    undef_macros=["NDEBUG"]),
+            ],
+            cmdclass={
+                'build_ext': BuildExtension
+            }
+        )
 
         from featup.util import norm, unnorm
         models = {o: torch.hub.load("mhamilton723/FeatUp", o) for o in options}