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Added reference adapters, many bug fixes, more ip adapter work and customizability

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This commit is contained in:
Jaret Burkett
2024-01-01 17:15:53 -07:00
parent bafacf3b65
commit afc231efc1
7 changed files with 510 additions and 30 deletions
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12
toolkit/basic.py
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@@ -31,12 +31,18 @@ def get_mean_std(tensor):
def adain(content_features, style_features):
# Assumes that the content and style features are of shape (batch_size, channels, width, height)
dims = [2, 3]
if len(content_features.shape) == 3:
# content_features = content_features.unsqueeze(0)
# style_features = style_features.unsqueeze(0)
dims = [1]
# Step 1: Calculate mean and variance of content features
content_mean, content_var = torch.mean(content_features, dim=[2, 3], keepdim=True), torch.var(content_features,
dim=[2, 3],
content_mean, content_var = torch.mean(content_features, dim=dims, keepdim=True), torch.var(content_features,
dim=dims,
keepdim=True)
# Step 2: Calculate mean and variance of style features
style_mean, style_var = torch.mean(style_features, dim=[2, 3], keepdim=True), torch.var(style_features, dim=[2, 3],
style_mean, style_var = torch.mean(style_features, dim=dims, keepdim=True), torch.var(style_features, dim=dims,
keepdim=True)
# Step 3: Normalize content features