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cmdr2 2022-11-25 23:54:08 +05:30 committed by GitHub
parent a1d75d40aa
commit bee67fd883
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1 changed files with 5 additions and 4 deletions
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9
ui/sd_internal/runtime.py
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@ -614,7 +614,7 @@ def do_mk_img(req: Request):
if handler == _txt2img: if handler == _txt2img:
x_samples = _txt2img(req.width, req.height, req.num_outputs, req.num_inference_steps, req.guidance_scale, None, opt_C, opt_f, opt_ddim_eta, c, uc, opt_seed, img_callback, mask, req.sampler) x_samples = _txt2img(req.width, req.height, req.num_outputs, req.num_inference_steps, req.guidance_scale, None, opt_C, opt_f, opt_ddim_eta, c, uc, opt_seed, img_callback, mask, req.sampler)
else: else:
x_samples = _img2img(init_latent, t_enc, batch_size, req.guidance_scale, c, uc, req.num_inference_steps, opt_ddim_eta, opt_seed, img_callback, mask) x_samples = _img2img(init_latent, t_enc, batch_size, req.guidance_scale, c, uc, req.num_inference_steps, opt_ddim_eta, opt_seed, img_callback, mask, opt_C, req.height, req.width, opt_f)
if req.stream_progress_updates: if req.stream_progress_updates:
yield from x_samples yield from x_samples
@ -806,7 +806,7 @@ def _txt2img(opt_W, opt_H, opt_n_samples, opt_ddim_steps, opt_scale, start_code,
) )
yield from samples_ddim yield from samples_ddim
def _img2img(init_latent, t_enc, batch_size, opt_scale, c, uc, opt_ddim_steps, opt_ddim_eta, opt_seed, img_callback, mask): def _img2img(init_latent, t_enc, batch_size, opt_scale, c, uc, opt_ddim_steps, opt_ddim_eta, opt_seed, img_callback, mask, opt_C=1, opt_H=1, opt_W=1, opt_f=1):
# encode (scaled latent) # encode (scaled latent)
x_T = None if mask is None else init_latent x_T = None if mask is None else init_latent
@ -821,8 +821,9 @@ def _img2img(init_latent, t_enc, batch_size, opt_scale, c, uc, opt_ddim_steps, o
#samples = sampler.decode(z_enc, c, t_enc, unconditional_guidance_scale=opt.scale,unconditional_conditioning=uc, ) #samples = sampler.decode(z_enc, c, t_enc, unconditional_guidance_scale=opt.scale,unconditional_conditioning=uc, )
samples_ddim = sampler.sample( samples_ddim = sampler.sample(
S=t_enc, t_enc,
batch_size=batch_size, batch_size,
shape = [opt_C, opt_H // opt_f, opt_W // opt_f],
conditioning=c, conditioning=c,
x0=z_enc, x0=z_enc,
unconditional_guidance_scale=opt_scale, unconditional_guidance_scale=opt_scale,