Update app.py

app.py

@@ -18,18 +18,8 @@ if huggingface_token is None:
     raise ValueError("Hugging Face token not found. Please set the HUGGINGFACE_TOKEN environment variable.")
 
 
-# # Define a custom transform for Gaussian blur
-# def gaussian_blur(x, p=0.5, kernel_size_min=3, kernel_size_max=9, sigma_min=0.1, sigma_max=2):
-#     if x.ndim == 4:
-#         for i in range(x.shape[0]):
-#             if random.random() < p:
-#                 kernel_size = random.randrange(kernel_size_min, kernel_size_max + 1, 2)
-#                 sigma = random.uniform(sigma_min, sigma_max)
-#                 x[i] = GaussianBlur(kernel_size=kernel_size, sigma=sigma)(x[i])
-#     return x
-
 # Define a custom transform for Gaussian blur
-def gaussian_blur(x, p=0.5, kernel_size_min=3, kernel_size_max=20, sigma_min=0.1, sigma_max=3):
+def gaussian_blur(x, p=0.5, kernel_size_min=3, kernel_size_max=9, sigma_min=0.1, sigma_max=2):
     if x.ndim == 4:
         for i in range(x.shape[0]):
             if random.random() < p:
@@ -38,6 +28,16 @@ def gaussian_blur(x, p=0.5, kernel_size_min=3, kernel_size_max=20, sigma_min=0.1
                 x[i] = GaussianBlur(kernel_size=kernel_size, sigma=sigma)(x[i])
     return x
 
+# # Define a custom transform for Gaussian blur
+# def gaussian_blur(x, p=0.5, kernel_size_min=3, kernel_size_max=20, sigma_min=0.1, sigma_max=3):
+#     if x.ndim == 4:
+#         for i in range(x.shape[0]):
+#             if random.random() < p:
+#                 kernel_size = random.randrange(kernel_size_min, kernel_size_max + 1, 2)
+#                 sigma = random.uniform(sigma_min, sigma_max)
+#                 x[i] = GaussianBlur(kernel_size=kernel_size, sigma=sigma)(x[i])
+#     return x
+
 # this function only describes how much a singular value in al ist stands out.
 # if all values in the lsit are high or low this is 1
 # the smaller the proportiopn of number of disimilar vlaues are to other more similar values the lower this number