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@@ -20,6 +20,8 @@ opCLIPTextEncode = CLIPTextEncode()
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opEmptyLatentImage = EmptyLatentImage()
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opVAEDecode = VAEDecode()
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cv2_is_top = False
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class StableDiffusionModel:
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def __init__(self, unet, vae, clip, clip_vision):
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@@ -62,6 +64,7 @@ def get_previewer(device, latent_format):
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taesd = TAESD(None, taesd_decoder_path).to(device)
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def preview_function(x0, step, total_steps):
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global cv2_is_top
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with torch.no_grad():
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x_sample = taesd.decoder(x0).detach() * 255.0
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x_sample = einops.rearrange(x_sample, 'b c h w -> b h w c')
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@@ -70,7 +73,9 @@ def get_previewer(device, latent_format):
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flag = f'OpenCV Diffusion Preview {i}'
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cv2.imshow(flag, s)
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cv2.setWindowTitle(flag, f'Preview Image {i} [{step}/{total_steps}]')
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cv2.setWindowProperty(flag, cv2.WND_PROP_TOPMOST, 1)
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if not cv2_is_top:
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cv2.setWindowProperty(flag, cv2.WND_PROP_TOPMOST, 1)
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cv2_is_top = True
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cv2.waitKey(1)
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taesd.preview = preview_function
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@@ -79,6 +84,7 @@ def get_previewer(device, latent_format):
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def close_all_preview():
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cv2_is_top = False
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cv2.destroyAllWindows()
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