Update some descriptions

nodes/image_nodes.py

@@ -2717,6 +2717,7 @@ class FastPreview:
     FUNCTION = "preview"
     CATEGORY = "KJNodes/experimental"
     OUTPUT_NODE = True
+    DESCRIPTION = "Experimental node for faster image previews by displaying through base64 it without saving to disk."
 
     def preview(self, image, format, quality):        
         pil_image = to_pil_image(image[0].permute(2, 0, 1))
@@ -2884,6 +2885,7 @@ class ImageCropByMask:
     RETURN_NAMES = ("image", )
     FUNCTION = "crop"
     CATEGORY = "KJNodes/image"
+    DESCRIPTION = "Crops the input images based on the provided mask."
 
     def crop(self, image, mask):
         B, H, W, C = image.shape
@@ -3097,7 +3099,7 @@ class ImagePadKJ:
     RETURN_NAMES = ("images", "masks",)
     FUNCTION = "pad"
     CATEGORY = "KJNodes/image"
-    DESCRIPTION = "Crops the input images based on the provided masks."
+    DESCRIPTION = "Pad the input image and optionally mask with the specified padding."
         
     def pad(self, image, left, right, top, bottom, extra_padding, color, pad_mode, mask=None):
         B, H, W, C = image.shape

nodes/mask_nodes.py

@@ -1291,6 +1291,7 @@ class SeparateMasks:
     FUNCTION = "separate"
     CATEGORY = "KJNodes/masking"
     OUTPUT_NODE = True
+    DESCRIPTION = "Separates a mask into multiple masks based on the size of the connected components."
 
     def polygon_to_mask(self, polygon, shape):
         mask = np.zeros((shape[0], shape[1]), dtype=np.uint8)  # Fixed shape handling

nodes/nodes.py

@@ -2318,8 +2318,10 @@ class ImageNoiseAugmentation:
 
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "add_noise"
-
     CATEGORY = "KJNodes/image"
+    DESCRIPTION = """
+    Add noise to an image.  
+    """
 
     def add_noise(self, image, noise_aug_strength, seed):
         torch.manual_seed(seed)
@@ -2411,7 +2413,6 @@ class VAELoaderKJ:
         
     RETURN_TYPES = ("VAE",)
     FUNCTION = "load_vae"
-
     CATEGORY = "KJNodes/vae"
 
     def load_vae(self, vae_name, device, weight_dtype):
@@ -2478,6 +2479,10 @@ class ScheduledCFGGuidance:
     RETURN_TYPES = ("GUIDER",)
     FUNCTION = "get_guider"
     CATEGORY = "KJNodes/experimental"
+    DESCRiPTION = """
+CFG Guider that allows for scheduled CFG changes over steps, the steps outside the range will use CFG 1.0 thus being processed faster.  
+cfg input can be a list of floats matching step count, or a single float for all steps.  
+"""
 
     def get_guider(self, model, cfg, positive, negative, start_percent, end_percent):
         guider = Guider_ScheduledCFG(model)