Converts Sepia Node to generic ColorTint

You can tint any color by modifying sepia scale weights

post_processing/color_tint.py

@@ -0,0 +1,66 @@
+import torch
+
+class ColorTint:
+    def __init__(self):
+        pass
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+                "strength": ("FLOAT", {
+                    "default": 1.0,
+                    "min": 0.1,
+                    "max": 1.0,
+                    "step": 0.1
+                }),
+                "mode": (["sepia", "red", "green", "blue", "cyan", "magenta", "yellow", "purple", "orange", "warm", "cool",  "lime", "navy", "vintage", "rose", "teal", "maroon", "peach", "lavender", "olive"],),
+            },
+        }
+
+    RETURN_TYPES = ("IMAGE",)
+    FUNCTION = "color_tint"
+
+    CATEGORY = "postprocessing/Color Adjustments"
+
+    def color_tint(self, image: torch.Tensor, strength: float, mode: str = "sepia"):
+        if strength == 0:
+            return (image,)
+
+        sepia_weights = torch.tensor([0.2989, 0.5870, 0.1140]).view(1, 1, 1, 3).to(image.device)
+
+        mode_filters = {
+            "sepia": torch.tensor([1.0, 0.8, 0.6]),
+            "red": torch.tensor([1.0, 0.6, 0.6]),
+            "green": torch.tensor([0.6, 1.0, 0.6]),
+            "blue": torch.tensor([0.6, 0.8, 1.0]),
+            "cyan": torch.tensor([0.6, 1.0, 1.0]),
+            "magenta": torch.tensor([1.0, 0.6, 1.0]),
+            "yellow": torch.tensor([1.0, 1.0, 0.6]),
+            "purple": torch.tensor([0.8, 0.6, 1.0]),
+            "orange": torch.tensor([1.0, 0.7, 0.3]),
+            "warm": torch.tensor([1.0, 0.9, 0.7]),
+            "cool": torch.tensor([0.7, 0.9, 1.0]),
+            "lime": torch.tensor([0.7, 1.0, 0.3]),
+            "navy": torch.tensor([0.3, 0.4, 0.7]),
+            "vintage": torch.tensor([0.9, 0.85, 0.7]),
+            "rose": torch.tensor([1.0, 0.8, 0.9]),
+            "teal": torch.tensor([0.3, 0.8, 0.8]),
+            "maroon": torch.tensor([0.7, 0.3, 0.5]),
+            "peach": torch.tensor([1.0, 0.8, 0.6]),
+            "lavender": torch.tensor([0.8, 0.6, 1.0]),
+            "olive": torch.tensor([0.6, 0.7, 0.4]),
+        }
+
+        scale_filter = mode_filters[mode].view(1, 1, 1, 3).to(image.device)
+
+        grayscale = torch.sum(image * sepia_weights, dim=-1, keepdim=True)
+        tinted = grayscale * scale_filter
+
+        result = tinted * strength + image * (1 - strength)
+        return (result,)
+
+NODE_CLASS_MAPPINGS = {
+    "ColorTint": ColorTint
+}