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Noise fix #5

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Noise fix #5

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1bc67dc
Thanks to @patrickvonplaten for this fix. [Depth2Img] Correct timeste…
madrang Dec 26, 2022
2bdb5ba
Thanks to @patrickvonplaten for this fix. Correct timestep for initia…
madrang Dec 27, 2022
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2 changes: 1 addition & 1 deletion scripts/gradio/depth2img.py
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Original file line number Diff line number Diff line change
Expand Up @@ -100,7 +100,7 @@ def paint(sampler, image, prompt, t_enc, seed, scale, num_samples=1, callback=No
if not do_full_sample:
# encode (scaled latent)
z_enc = sampler.stochastic_encode(
z, torch.tensor([t_enc] * num_samples).to(model.device))
z, torch.tensor([t_enc - 1] * num_samples).to(model.device))
else:
z_enc = torch.randn_like(z)
# decode it
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2 changes: 1 addition & 1 deletion scripts/img2img.py
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Expand Up @@ -244,7 +244,7 @@ def main():
c = model.get_learned_conditioning(prompts)

# encode (scaled latent)
z_enc = sampler.stochastic_encode(init_latent, torch.tensor([t_enc] * batch_size).to(device))
z_enc = sampler.stochastic_encode(init_latent, torch.tensor([t_enc - 1] * batch_size).to(device))
# decode it
samples = sampler.decode(z_enc, c, t_enc, unconditional_guidance_scale=opt.scale,
unconditional_conditioning=uc, )
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2 changes: 1 addition & 1 deletion scripts/streamlit/depth2img.py
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Expand Up @@ -93,7 +93,7 @@ def paint(sampler, image, prompt, t_enc, seed, scale, num_samples=1, callback=No
uc_full = {"c_concat": [c_cat], "c_crossattn": [uc_cross]}
if not do_full_sample:
# encode (scaled latent)
z_enc = sampler.stochastic_encode(z, torch.tensor([t_enc] * num_samples).to(model.device))
z_enc = sampler.stochastic_encode(z, torch.tensor([t_enc - 1] * num_samples).to(model.device))
else:
z_enc = torch.randn_like(z)
# decode it
Expand Down