nodes/spacepxl-ComfyUI-Image-Filters
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relight simple xy -> xyz

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spacepxl
2024-10-30 00:07:11 -04:00
parent 0a6031e9ca
commit fb0a1ae38d
1 changed files with 5 additions and 4 deletions
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nodes.py
+5 -4
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@@ -1199,8 +1199,9 @@ class RelightSimple:
"required": {
"image": ("IMAGE",),
"normals": ("IMAGE",),
"x_dir": ("FLOAT", {"default": 0.0, "min": -1.5, "max": 1.5, "step": 0.01}),
"y_dir": ("FLOAT", {"default": 0.0, "min": -1.5, "max": 1.5, "step": 0.01}),
"x": ("FLOAT", {"default": 0.0, "min": -1.0, "max": 1.0, "step": 0.001}),
"y": ("FLOAT", {"default": 0.0, "min": -1.0, "max": 1.0, "step": 0.001}),
"z": ("FLOAT", {"default": 1.0, "min": -1.0, "max": 1.0, "step": 0.001}),
"brightness": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 100, "step": 0.01}),
},
}
@@ -1210,12 +1211,12 @@ class RelightSimple:
CATEGORY = "image/filters"
def relight(self, image, normals, x_dir, y_dir, brightness):
def relight(self, image, normals, x, y, z, brightness):
if image.shape[0] != normals.shape[0]:
raise Exception("Batch size for image and normals must match")
norm = normals.detach().clone() * 2 - 1
norm = torch.nn.functional.interpolate(norm.movedim(-1,1), size=(image.shape[1], image.shape[2]), mode='bilinear').movedim(1,-1)
light = torch.tensor([x_dir, y_dir, abs(1 - math.sqrt(x_dir ** 2 + y_dir ** 2) * 0.7)])
light = torch.tensor([x, y, z])
light = torch.nn.functional.normalize(light, dim=0)
diffuse = norm[:,:,:,0] * light[0] + norm[:,:,:,1] * light[1] + norm[:,:,:,2] * light[2]