LUT application strength

2026-04-08 13:59:54 +03:00
parent 3207ee7f1b
commit c15ade5f7d
1 changed files with 9 additions and 2 deletions
@@ -225,16 +225,23 @@ class VCGApplyLUT(IO.ComfyNode):
        return IO.Schema(
            node_id="VCGApplyLUT", display_name="Apply 3D LUT (VCG)", category="video/color-grading",
            description="Apply a generated 3D color LUT to images",
-            inputs=[IO.Image.Input("images"), VCG_LUT.Input("lut")],
+            inputs=[
+                IO.Image.Input("images"),
+                VCG_LUT.Input("lut"),
+                IO.Float.Input("strength", default=1.0, min=0.0, max=2.0, step=0.01, optional=True, tooltip="LUT strength: 0=no effect, 1=full effect, >1=exaggerated"),
+            ],
            outputs=[IO.Image.Output()],
        )


    @classmethod
-    def execute(cls, images, lut):
+    def execute(cls, images, lut, strength=1.0):
        device = comfy.model_management.intermediate_device()
        dtype = images.dtype
        lut_3d = torch.from_numpy(lut["values"].reshape(16, 16, 16, 3).astype(np.float32))
+        if strength != 1.0:
+            identity = torch.from_numpy(make_identity_lut(16).reshape(16, 16, 16, 3).astype(np.float32))
+            lut_3d = identity + strength * (lut_3d - identity)
        lut_vol = lut_3d.permute(3, 0, 1, 2).unsqueeze(0).to(device=device, dtype=dtype)
        B = images.shape[0]
        output = torch.empty_like(images)