test

app.py

@@ -5,9 +5,7 @@ import glob
 import matplotlib.pyplot as plt
 import torch
 import torchvision.transforms as T
-from PIL import Image
 import gradio as gr
-from featup.util import norm, unnorm, pca, remove_axes
 from pytorch_lightning import seed_everything
 import os
 import requests
@@ -16,6 +14,7 @@ import spaces
 
 
 def plot_feats(image, lr, hr):
+    from featup.util import pca, remove_axes
     assert len(image.shape) == len(lr.shape) == len(hr.shape) == 3
     seed_everything(0)
     [lr_feats_pca, hr_feats_pca], _ = pca(
@@ -116,6 +115,7 @@ def upsample_features(image, model_option):
     subprocess.check_call(
         ["pip", "install", "git+https://github.com/mhamilton723/FeatUp"])
 
+    from featup.util import norm, unnorm
     models = {o: torch.hub.load("mhamilton723/FeatUp", o) for o in options}
 
     # Image preprocessing