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https://github.com/comfyanonymous/ComfyUI.git
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Latent2rgb for LTXV
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kijai
parent
5943fbf457
commit
04c0dd0737
@ -409,8 +409,137 @@ class LTXV(LatentFormat):
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class LTXAV(LTXV):
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def __init__(self):
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self.latent_rgb_factors = None
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self.latent_rgb_factors_bias = None
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self.latent_rgb_factors = [
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[ 0.0350, 0.0159, 0.0132],
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[ 0.0025, -0.0021, -0.0003],
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[ 0.0286, 0.0028, 0.0020],
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[ 0.0280, -0.0114, -0.0202],
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[-0.0186, 0.0073, 0.0092],
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[ 0.0027, 0.0097, -0.0113],
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[-0.0069, -0.0032, -0.0024],
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[-0.0323, -0.0370, -0.0457],
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[ 0.0174, 0.0164, 0.0106],
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[-0.0097, 0.0061, 0.0035],
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[-0.0130, -0.0042, -0.0012],
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[-0.0102, -0.0002, -0.0091],
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[-0.0025, 0.0063, 0.0161],
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[ 0.0003, 0.0037, 0.0108],
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[ 0.0152, 0.0082, 0.0143],
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[ 0.0317, 0.0203, 0.0312],
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[-0.0092, -0.0233, -0.0119],
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[-0.0405, -0.0226, -0.0023],
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[ 0.0376, 0.0397, 0.0352],
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[ 0.0171, -0.0043, -0.0095],
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[ 0.0482, 0.0341, 0.0213],
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[ 0.0031, -0.0046, -0.0018],
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[-0.0486, -0.0383, -0.0294],
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[-0.0071, -0.0272, -0.0123],
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[ 0.0320, 0.0218, 0.0289],
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[ 0.0327, 0.0088, -0.0116],
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[-0.0098, -0.0240, -0.0111],
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[ 0.0094, -0.0116, 0.0021],
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[ 0.0309, 0.0092, 0.0165],
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[-0.0065, -0.0077, -0.0107],
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[ 0.0179, 0.0114, 0.0038],
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[-0.0018, -0.0030, -0.0026],
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[-0.0002, 0.0076, -0.0029],
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[-0.0131, -0.0059, -0.0170],
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[ 0.0055, 0.0066, -0.0038],
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[ 0.0154, 0.0063, 0.0090],
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[ 0.0186, 0.0175, 0.0188],
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[-0.0166, -0.0381, -0.0428],
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[ 0.0121, 0.0015, -0.0153],
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[ 0.0118, 0.0050, 0.0019],
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[ 0.0125, 0.0259, 0.0231],
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[ 0.0046, 0.0130, 0.0081],
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[ 0.0271, 0.0250, 0.0250],
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[-0.0054, -0.0347, -0.0326],
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[-0.0438, -0.0262, -0.0228],
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[-0.0191, -0.0256, -0.0173],
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[-0.0205, -0.0058, 0.0042],
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[ 0.0404, 0.0434, 0.0346],
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[-0.0242, -0.0177, -0.0146],
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[ 0.0161, 0.0223, 0.0168],
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[-0.0240, -0.0320, -0.0299],
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[-0.0019, 0.0043, 0.0008],
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[-0.0060, -0.0133, -0.0244],
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[-0.0048, -0.0225, -0.0167],
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[ 0.0267, 0.0133, 0.0152],
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[ 0.0222, 0.0167, 0.0028],
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[ 0.0015, -0.0062, 0.0013],
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[-0.0241, -0.0178, -0.0079],
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[ 0.0040, -0.0081, -0.0097],
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[-0.0064, 0.0133, -0.0011],
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[-0.0204, -0.0231, -0.0304],
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[ 0.0011, -0.0011, 0.0145],
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[-0.0283, -0.0259, -0.0260],
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[ 0.0038, 0.0171, -0.0029],
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[ 0.0637, 0.0424, 0.0409],
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[ 0.0092, 0.0163, 0.0188],
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[ 0.0082, 0.0055, -0.0179],
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[-0.0177, -0.0286, -0.0147],
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[ 0.0171, 0.0242, 0.0398],
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[-0.0129, 0.0095, -0.0071],
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[-0.0154, 0.0036, 0.0128],
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[-0.0081, -0.0009, 0.0118],
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[-0.0067, -0.0178, -0.0230],
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[-0.0022, -0.0125, -0.0003],
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[-0.0032, -0.0039, -0.0022],
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[-0.0005, -0.0127, -0.0131],
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[-0.0143, -0.0157, -0.0165],
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[-0.0262, -0.0263, -0.0270],
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[ 0.0063, 0.0127, 0.0178],
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[ 0.0092, 0.0133, 0.0150],
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[-0.0106, -0.0068, 0.0032],
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[-0.0214, -0.0022, 0.0171],
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[-0.0104, -0.0266, -0.0362],
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[ 0.0021, 0.0048, -0.0005],
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[ 0.0345, 0.0431, 0.0402],
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[-0.0275, -0.0110, -0.0195],
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[ 0.0203, 0.0251, 0.0224],
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[ 0.0016, -0.0037, -0.0094],
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[ 0.0241, 0.0198, 0.0114],
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[-0.0003, 0.0027, 0.0141],
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[ 0.0012, -0.0052, -0.0084],
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[ 0.0057, -0.0028, -0.0163],
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[-0.0488, -0.0545, -0.0509],
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[-0.0076, -0.0025, -0.0014],
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[-0.0249, -0.0142, -0.0367],
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[ 0.0136, 0.0041, 0.0135],
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[ 0.0007, 0.0034, -0.0053],
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[-0.0068, -0.0109, 0.0029],
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[ 0.0006, -0.0237, -0.0094],
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[-0.0149, -0.0177, -0.0131],
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[-0.0105, 0.0039, 0.0216],
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[ 0.0242, 0.0200, 0.0180],
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[-0.0339, -0.0153, -0.0195],
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[ 0.0104, 0.0151, 0.0120],
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[-0.0043, 0.0089, 0.0047],
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[ 0.0157, -0.0030, 0.0008],
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[ 0.0126, 0.0102, -0.0040],
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[ 0.0040, 0.0114, 0.0137],
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[ 0.0423, 0.0473, 0.0436],
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[-0.0128, -0.0066, -0.0152],
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[-0.0337, -0.0087, -0.0026],
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[-0.0052, 0.0235, 0.0291],
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[ 0.0079, 0.0154, 0.0260],
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[-0.0539, -0.0377, -0.0358],
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[-0.0188, 0.0062, -0.0035],
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[-0.0186, 0.0041, -0.0083],
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[ 0.0045, -0.0049, 0.0053],
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[ 0.0172, 0.0071, 0.0042],
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[-0.0003, -0.0078, -0.0096],
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[-0.0209, -0.0132, -0.0135],
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[-0.0074, 0.0017, 0.0099],
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[-0.0038, 0.0070, 0.0014],
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[-0.0013, -0.0017, 0.0073],
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[ 0.0030, 0.0105, 0.0105],
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[ 0.0154, -0.0168, -0.0235],
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[-0.0108, -0.0038, 0.0047],
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[-0.0298, -0.0347, -0.0436],
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[-0.0206, -0.0189, -0.0139]
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]
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self.latent_rgb_factors_bias = [0.2796, 0.1101, -0.0047]
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class HunyuanVideo(LatentFormat):
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latent_channels = 16
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@ -753,7 +753,7 @@ class SamplerCustom(io.ComfyNode):
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noise_mask = latent["noise_mask"]
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x0_output = {}
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callback = latent_preview.prepare_callback(model, sigmas.shape[-1] - 1, x0_output)
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callback = latent_preview.prepare_callback(model, sigmas.shape[-1] - 1, x0_output, shape=latent_image.shape)
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disable_pbar = not comfy.utils.PROGRESS_BAR_ENABLED
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samples = comfy.sample.sample_custom(model, noise, cfg, sampler, sigmas, positive, negative, latent_image, noise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=noise_seed)
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@ -944,7 +944,7 @@ class SamplerCustomAdvanced(io.ComfyNode):
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noise_mask = latent["noise_mask"]
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x0_output = {}
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callback = latent_preview.prepare_callback(guider.model_patcher, sigmas.shape[-1] - 1, x0_output)
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callback = latent_preview.prepare_callback(guider.model_patcher, sigmas.shape[-1] - 1, x0_output, shape=latent_image.shape)
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disable_pbar = not comfy.utils.PROGRESS_BAR_ENABLED
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samples = guider.sample(noise.generate_noise(latent), latent_image, sampler, sigmas, denoise_mask=noise_mask, callback=callback, disable_pbar=disable_pbar, seed=noise.seed)
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@ -7,6 +7,7 @@ import comfy.model_management
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import folder_paths
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import comfy.utils
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import logging
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import math
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default_preview_method = args.preview_method
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@ -109,7 +110,7 @@ def get_previewer(device, latent_format):
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previewer = Latent2RGBPreviewer(latent_format.latent_rgb_factors, latent_format.latent_rgb_factors_bias, latent_format.latent_rgb_factors_reshape)
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return previewer
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def prepare_callback(model, steps, x0_output_dict=None):
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def prepare_callback(model, steps, x0_output_dict=None, shape=None):
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preview_format = "JPEG"
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if preview_format not in ["JPEG", "PNG"]:
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preview_format = "JPEG"
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@ -121,6 +122,10 @@ def prepare_callback(model, steps, x0_output_dict=None):
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if x0_output_dict is not None:
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x0_output_dict["x0"] = x0
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if x0.ndim == 3:
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cut = math.prod(shape[1:])
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x0 = x0[:, :, :cut].reshape([x0.shape[0]] + list(shape)[1:])
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preview_bytes = None
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if previewer:
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preview_bytes = previewer.decode_latent_to_preview_image(preview_format, x0)
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2
nodes.py
2
nodes.py
@ -1504,7 +1504,7 @@ def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive,
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if "noise_mask" in latent:
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noise_mask = latent["noise_mask"]
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callback = latent_preview.prepare_callback(model, steps)
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callback = latent_preview.prepare_callback(model, steps, shape=latent_image.shape)
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disable_pbar = not comfy.utils.PROGRESS_BAR_ENABLED
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samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
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denoise=denoise, disable_noise=disable_noise, start_step=start_step, last_step=last_step,
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