fix SD norm

app.py

@@ -461,15 +461,18 @@ def extract_video_frames(video_path, max_frames=100):
     # return as list of PIL images
     return [(Image.fromarray(frames[i]), "") for i in range(frames.shape[0])]
 
-def transform_image(image, resolution=(1024, 1024)):
+def transform_image(image, resolution=(1024, 1024), stablediffusion=False):
     image = image.convert('RGB').resize(resolution, Image.LANCZOS)
     # Convert to torch tensor
     image = torch.tensor(np.array(image).transpose(2, 0, 1)).float()
     image = image / 255
     # Normalize
-    mean = [0.485, 0.456, 0.406]
-    std = [0.229, 0.224, 0.225]
-    image = (image - torch.tensor(mean).view(3, 1, 1)) / torch.tensor(std).view(3, 1, 1)
+    if not stablediffusion:
+        mean = [0.485, 0.456, 0.406]
+        std = [0.229, 0.224, 0.225]
+        image = (image - torch.tensor(mean).view(3, 1, 1)) / torch.tensor(std).view(3, 1, 1)
+    if stablediffusion:
+        image = image * 2 - 1
     return image
 
 def plot_one_image_36_grid(original_image, tsne_rgb_images):
@@ -617,7 +620,8 @@ def run_fn(
     else:
         resolution = RES_DICT[model_name]
     images = [tup[0] for tup in images]
-    images = [transform_image(image, resolution=resolution) for image in images]
+    stablediffusion = True if "Diffusion" in model_name else False
+    images = [transform_image(image, resolution=resolution, stablediffusion=stablediffusion) for image in images]
     images = torch.stack(images)
     
     
@@ -1401,9 +1405,9 @@ with demo:
         with gr.Column():
             gr.Markdown("###### Running out of GPU? Try [Demo](https://ncut-pytorch.readthedocs.io/en/latest/demo/) hosted at UPenn")
 
-# # for local development
-# if os.path.exists("/hf_token.txt"):
-#     os.environ["HF_ACCESS_TOKEN"] = open("/hf_token.txt").read().strip()
+# for local development
+if os.path.exists("/hf_token.txt"):
+    os.environ["HF_ACCESS_TOKEN"] = open("/hf_token.txt").read().strip()
 
 if DOWNLOAD_ALL_MODELS_DATASETS:
     from ncut_pytorch.backbone import download_all_models