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applied workaround for gradio 3.2

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AUTOMATIC 2022-09-01 22:05:31 +03:00
parent 8d45b3be18
commit 0b8ca64aa2
2 changed files with 18 additions and 14 deletions
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2
requirements.txt
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@ -1,6 +1,6 @@
basicsr basicsr
gfpgan gfpgan
gradio==3.1.5 gradio
numpy numpy
Pillow Pillow
realesrgan realesrgan

30
webui.py
View file

@ -80,6 +80,10 @@ batch_cond_uncond = cmd_opts.always_batch_cond_uncond or not (cmd_opts.lowvram o
queue_lock = threading.Lock() queue_lock = threading.Lock()
def gr_show(visible=True):
return {"visible": visible, "__type__": "update"}
class State: class State:
interrupted = False interrupted = False
job = "" job = ""
@ -1132,7 +1136,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
# we manually generate all input noises because each one should have a specific seed # we manually generate all input noises because each one should have a specific seed
x = create_random_tensors([opt_C, p.height // opt_f, p.width // opt_f], seeds=seeds) x = create_random_tensors([opt_C, p.height // opt_f, p.width // opt_f], seeds=seeds)
if p.n_iter > 0: if p.n_iter > 1:
state.job = f"Batch {n+1} out of {p.n_iter}" state.job = f"Batch {n+1} out of {p.n_iter}"
samples_ddim = p.sample(x=x, conditioning=c, unconditional_conditioning=uc) samples_ddim = p.sample(x=x, conditioning=c, unconditional_conditioning=uc)
@ -1728,16 +1732,16 @@ with gr.Blocks(analytics_enabled=False) as img2img_interface:
is_upscale = mode == 3 is_upscale = mode == 3
return { return {
init_img: gr.update(visible=not is_inpaint), init_img: gr_show(not is_inpaint),
init_img_with_mask: gr.update(visible=is_inpaint), init_img_with_mask: gr_show(is_inpaint),
mask_blur: gr.update(visible=is_inpaint), mask_blur: gr_show(is_inpaint),
inpainting_fill: gr.update(visible=is_inpaint), inpainting_fill: gr_show(is_inpaint),
prompt_matrix: gr.update(visible=is_classic), prompt_matrix: gr_show(is_classic),
batch_count: gr.update(visible=not is_upscale), batch_count: gr_show(not is_upscale),
batch_size: gr.update(visible=not is_loopback), batch_size: gr_show(not is_loopback),
sd_upscale_upscaler_name: gr.update(visible=is_upscale), sd_upscale_upscaler_name: gr_show(is_upscale),
sd_upscale_overlap: gr.Slider.update(visible=is_upscale), sd_upscale_overlap:gr_show(is_upscale),
inpaint_full_res: gr.update(visible=is_inpaint), inpaint_full_res: gr_show(is_inpaint),
} }
switch_mode.change( switch_mode.change(
@ -1979,9 +1983,9 @@ sd_model = load_model_from_config(sd_config, cmd_opts.ckpt)
sd_model = (sd_model if cmd_opts.no_half else sd_model.half()) sd_model = (sd_model if cmd_opts.no_half else sd_model.half())
if cmd_opts.lowvram or cmd_opts.medvram: if cmd_opts.lowvram or cmd_opts.medvram:
setup_for_low_vram(sd_model) setup_for_low_vram(sd_model)
else: else:
sd_model = sd_model.to(device) sd_model = sd_model.to(device)
model_hijack = StableDiffusionModelHijack() model_hijack = StableDiffusionModelHijack()
model_hijack.hijack(sd_model) model_hijack.hijack(sd_model)