added SharpenFilterLatent

nodes.py

@@ -783,6 +783,40 @@ class AdainFilterLatent:
         latents_copy["samples"] = torch.lerp(latents["samples"], t, factor)
         return (latents_copy,)
 
+class SharpenFilterLatent:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "latents": ("LATENT", ),
+                "filter_size": ("INT", {"default": 1, "min": 1, "max": 128}),
+                "factor": ("FLOAT", {"default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01,  "round": 0.01}),
+            },
+        }
+
+    RETURN_TYPES = ("LATENT",)
+    FUNCTION = "filter_latent"
+
+    CATEGORY = "latent/filters"
+
+    def filter_latent(self, latents, filter_size, factor):
+        latents_copy = copy.deepcopy(latents)
+        t = latents_copy["samples"].movedim(1, -1) # [B x C x H x W] -> [B x H x W x C]
+        
+        d = filter_size * 2 + 1
+        t_blurred = cv_blur_tensor(t, d, d)
+        
+        t = t - t_blurred
+        t = t * factor
+        t = t + t_blurred
+        
+        t = t.movedim(-1, 1) # [B x H x W x C] -> [B x C x H x W]
+        latents_copy["samples"] = t
+        return (latents_copy,)
+
 class AdainImage:
     def __init__(self):
         pass
@@ -1673,6 +1707,7 @@ NODE_CLASS_MAPPINGS = {
     "InstructPixToPixConditioningAdvanced": InstructPixToPixConditioningAdvanced,
     "LatentNormalizeShuffle": LatentNormalizeShuffle,
     "PrintSigmas": PrintSigmas,
+    "SharpenFilterLatent": SharpenFilterLatent,
 }
 
 NODE_DISPLAY_NAME_MAPPINGS = {
@@ -1714,4 +1749,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "InstructPixToPixConditioningAdvanced": "InstructPixToPixConditioningAdvanced",
     "LatentNormalizeShuffle": "LatentNormalizeShuffle",
     "PrintSigmas": "PrintSigmas",
+    "SharpenFilterLatent": "Sharpen Filter (Latent)",
 }