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Add mask restore feature to streamlit, prevent color correction from modifying initial image when mask_restore is turned on

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This commit is contained in:
unnamedplugins 2022-09-13 10:57:07 -04:00
parent 84bb985134
commit 0c0e80d909
1 changed files with 31 additions and 17 deletions
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48
scripts/webui_streamlit.py
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@ -1644,17 +1644,28 @@ def img2img(prompt: str = '', init_info: any = None, init_info_mask: any = None,
if initial_seed is None:
initial_seed = seed
input_image = init_img
init_img = output_images[0]
if do_color_correction and correction_target is not None:
init_img = Image.fromarray(cv2.cvtColor(exposure.match_histograms(
cv2.cvtColor(
np.asarray(init_img),
cv2.COLOR_RGB2LAB
),
correction_target,
channel_axis=2
), cv2.COLOR_LAB2RGB).astype("uint8"))
init_img = Image.fromarray(
cv2.cvtColor(
exposure.match_histograms(
cv2.cvtColor(
np.asarray(init_img),
cv2.COLOR_RGB2LAB
),
correction_target,
channel_axis=2
),
cv2.COLOR_LAB2RGB).astype("uint8"))
if mask_restore is True:
color_mask = init_mask.filter(ImageFilter.GaussianBlur(mask_blur_strength))
color_mask = color_mask.convert('L')
source_image = input_image.convert('RGB')
target_image = init_img.convert('RGB')
init_img = Image.composite(source_image, target_image, color_mask)
if not random_seed_loopback:
seed = seed + 1
@ -2377,6 +2388,9 @@ def layout():
help="Ensure the sum of all weights add up to 1.0")
loopback = st.checkbox("Loopback.", value=defaults.img2img.loopback, help="Use images from previous batch when creating next batch.")
random_seed_loopback = st.checkbox("Random loopback seed.", value=defaults.img2img.random_seed_loopback, help="Random loopback seed")
img2img_mask_restore = st.checkbox("Only modify regenerated parts of image",
value=defaults.img2img.mask_restore,
help="Enable to restore the unmasked parts of the image with the input, may not blend as well but preserves detail")
save_individual_images = st.checkbox("Save individual images.", value=defaults.img2img.save_individual_images,
help="Save each image generated before any filter or enhancement is applied.")
save_grid = st.checkbox("Save grid",value=defaults.img2img.save_grid, help="Save a grid with all the images generated into a single image.")
@ -2517,15 +2531,15 @@ def layout():
new_mask = mask.resize((width, height))
try:
output_images, seed, info, stats = img2img(prompt=prompt, init_info=new_img, init_info_mask=new_mask, mask_mode=mask_mode, ddim_steps=st.session_state["sampling_steps"],
sampler_name=st.session_state["sampler_name"], n_iter=batch_count,
cfg_scale=cfg_scale, denoising_strength=st.session_state["denoising_strength"], variant_seed=variant_seed,
seed=seed, noise_mode=noise_mode, find_noise_steps=find_noise_steps, width=width, height=height, fp=defaults.general.fp, variant_amount=variant_amount,
ddim_eta=0.0, write_info_files=write_info_files, RealESRGAN_model=RealESRGAN_model,
separate_prompts=separate_prompts, normalize_prompt_weights=normalize_prompt_weights,
save_individual_images=save_individual_images, save_grid=save_grid,
group_by_prompt=group_by_prompt, save_as_jpg=save_as_jpg, use_GFPGAN=use_GFPGAN,
use_RealESRGAN=use_RealESRGAN if not loopback else False, loopback=loopback
output_images, seed, info, stats = img2img(prompt=prompt, init_info=new_img, init_info_mask=new_mask, mask_mode=mask_mode, mask_restore=img2img_mask_restore,
ddim_steps=st.session_state["sampling_steps"], sampler_name=st.session_state["sampler_name"], n_iter=batch_count,
cfg_scale=cfg_scale, denoising_strength=st.session_state["denoising_strength"], variant_seed=variant_seed,
seed=seed, noise_mode=noise_mode, find_noise_steps=find_noise_steps, width=width, height=height, fp=defaults.general.fp,
variant_amount=variant_amount, ddim_eta=0.0, write_info_files=write_info_files, RealESRGAN_model=RealESRGAN_model,
separate_prompts=separate_prompts, normalize_prompt_weights=normalize_prompt_weights,
save_individual_images=save_individual_images, save_grid=save_grid,
group_by_prompt=group_by_prompt, save_as_jpg=save_as_jpg, use_GFPGAN=use_GFPGAN,
use_RealESRGAN=use_RealESRGAN if not loopback else False, loopback=loopback
)
#show a message when the generation is complete.