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TAA/DLAA parameter tuning and cleanup

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MSXYZ-GenAI
2026-04-19 11:22:00 +03:00
parent 81103ed3eb
commit e2d850263b
1 changed files with 6 additions and 6 deletions
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VideoTAADLAA.py
+6 -6
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@@ -81,11 +81,11 @@ class VideoTAADLAA:
return {
"required": {
"images": ("IMAGE",),
"taa_strength": ("FLOAT", {"default": 0.65, "min": 0, "max": 1, "step": 0.05}),
"taa_strength": ("FLOAT", {"default": 0.60, "min": 0, "max": 1, "step": 0.05}),
"taa_alpha": ("FLOAT", {"default": 0.40, "min": 0, "max": 0.9, "step": 0.01}),
"motion_sensitivity": ("FLOAT", {"default": 0.05, "min": 0.01, "max": 0.5, "step": 0.01}),
"jitter_scale": ("FLOAT", {"default": 0.02, "min": 0, "max": 0.08, "step": 0.01}),
"dlaa_strength": ("FLOAT", {"default": 0.30, "min": 0, "max": 1, "step": 0.05}),
"dlaa_strength": ("FLOAT", {"default": 0.25, "min": 0, "max": 1, "step": 0.05}),
"edge_threshold": ("FLOAT", {"default": 0.25, "min": 0, "max": 0.5, "step": 0.01}),
"blur_radius": ("INT", {"default": 0, "min": 0, "max": 5, "step": 1}),
"reset_history": ("BOOLEAN", {"default": False}),
@@ -120,7 +120,7 @@ class VideoTAADLAA:
sx, sy = F.conv2d(gray, net.sobel_x, padding=1), F.conv2d(gray, net.sobel_y, padding=1)
edge = torch.sqrt(sx*sx + sy*sy + 1e-6)
mask = torch.sigmoid((edge - thr) * 15.0)
mask = torch.sigmoid((edge - thr) * 8.0)
blurred = F.avg_pool2d(F.pad(x, [blur]*4, mode="reflect"), blur*2+1, stride=1)
return x*(1-mask) + blurred*mask
@@ -157,9 +157,9 @@ class VideoTAADLAA:
mean_luma = torch.mean(luma, dim=(1, 2, 3), keepdim=True)
rgb = (rgb - mean_luma) * 1.02 + mean_luma
rgb[:, 2:3, :, :] += 0.025
rgb[:, 0:1, :, :] -= 0.010
rgb = torch.clamp(rgb, 0.0, 1.0)
rgb = torch.clamp((rgb - 0.5) * 1.02 + 0.5, 0.0, 1.0)
out_list.append(rgb.permute(0, 2, 3, 1).cpu())