Sygil-Dev/sygil-webui
1
1
Fork 0
mirror of https://github.com/Sygil-Dev/sygil-webui.git synced 2024-12-14 14:05:36 +03:00
Code Issues Projects Releases Wiki Activity

Added option to the Settings page to enable and disable the suggestion box.

Browse Source
This commit is contained in:
ZeroCool940711 2022-12-14 19:35:14 -07:00
parent 3e87802c9f
commit 3868b79b07
No known key found for this signature in database
GPG Key ID: 4E4072992B5BC640
6 changed files with 74 additions and 56 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

1
configs/webui/webui_streamlit.yaml
View File

@ -57,6 +57,7 @@ general:
n_rows: -1
no_verify_input: False
show_percent_in_tab_title: True
enable_suggestions: True
no_half: False
use_float16: False
precision: "autocast"

3
scripts/Settings.py
View File

@ -213,6 +213,9 @@ def layout():
help="Add the progress percent value to the page title on the tab on your browser. "
"This is useful in case you need to know how the generation is going while doign something else"
"in another tab on your browser. Default: True")
st.session_state["defaults"].general.enable_suggestions = st.checkbox("Enable Suggestions Box", value=st.session_state['defaults'].general.enable_suggestions,
help="Adds a suggestion box under the prompt when clicked. Default: True")
st.session_state["defaults"].daisi_app.running_on_daisi_io = st.checkbox("Running on Daisi.io?", value=st.session_state['defaults'].daisi_app.running_on_daisi_io,
help="Specify if we are running on app.Daisi.io . Default: False")

5
scripts/img2img.py
View File

@ -379,7 +379,10 @@ def layout():
#prompt = st.text_area("Input Text","")
placeholder = "A corgi wearing a top hat as an oil painting."
prompt = st.text_area("Input Text","", placeholder=placeholder, height=54)
sygil_suggestions.suggestion_area(placeholder)
if "defaults" in st.session_state:
if st.session_state["defaults"].general.enable_suggestions:
sygil_suggestions.suggestion_area(placeholder)
if "defaults" in st.session_state:
if st.session_state['defaults'].admin.global_negative_prompt:

3
scripts/sd_utils/__init__.py
View File

@ -109,6 +109,9 @@ try:
except:
pass
# disable diffusers telemetry
os.environ["DISABLE_TELEMETRY"] = "YES"
# remove some annoying deprecation warnings that show every now and then.
warnings.filterwarnings("ignore", category=DeprecationWarning)
warnings.filterwarnings("ignore", category=UserWarning)

5
scripts/txt2img.py
View File

@ -427,7 +427,10 @@ def layout():
#prompt = st.text_area("Input Text","")
placeholder = "A corgi wearing a top hat as an oil painting."
prompt = st.text_area("Input Text","", placeholder=placeholder, height=54)
sygil_suggestions.suggestion_area(placeholder)
if "defaults" in st.session_state:
if st.session_state["defaults"].general.enable_suggestions:
sygil_suggestions.suggestion_area(placeholder)
if "defaults" in st.session_state:
if st.session_state['defaults'].admin.global_negative_prompt:

113
scripts/txt2vid.py
View File

@ -942,12 +942,12 @@ class StableDiffusionWalkPipeline(DiffusionPipeline):
def diffuse(
pipe,
cond_embeddings, # text conditioning, should be (1, 77, 768)
cond_latents, # image conditioning, should be (1, 4, 64, 64)
num_inference_steps,
cfg_scale,
eta,
fps=30
):
cond_latents, # image conditioning, should be (1, 4, 64, 64)
num_inference_steps,
cfg_scale,
eta,
fps=30
):
torch_device = cond_latents.get_device()
@ -1133,7 +1133,7 @@ def load_diffusers_model(weights_path,torch_device):
if not os.path.exists(model_path + "/model_index.json"):
server_state["pipe"] = StableDiffusionPipeline.from_pretrained(
weights_path,
use_local_file=True,
#use_local_file=True,
use_auth_token=st.session_state["defaults"].general.huggingface_token,
torch_dtype=torch.float16 if st.session_state['defaults'].general.use_float16 else None,
revision="fp16" if not st.session_state['defaults'].general.no_half else None,
@ -1146,7 +1146,7 @@ def load_diffusers_model(weights_path,torch_device):
else:
server_state["pipe"] = StableDiffusionPipeline.from_pretrained(
model_path,
use_local_file=True,
#use_local_file=True,
torch_dtype=torch.float16 if st.session_state['defaults'].general.use_float16 else None,
revision="fp16" if not st.session_state['defaults'].general.no_half else None,
safety_checker=None, # Very important for videos...lots of false positives while interpolating
@ -1181,7 +1181,8 @@ def load_diffusers_model(weights_path,torch_device):
server_state['float16'] = st.session_state['defaults'].general.use_float16
server_state['no_half'] = st.session_state['defaults'].general.no_half
server_state['optimized'] = st.session_state['defaults'].general.optimized
#with no_rerun:
load_diffusers_model(weights_path, torch_device)
else:
logger.info("Tx2Vid Model already Loaded")
@ -1321,28 +1322,28 @@ def txt2vid(
with open(os.path.join(full_path , f'{slugify(str(seeds))}_config.json' if len(prompts) > 1 else "prompts_config.json"), "w") as outfile:
outfile.write(json.dumps(
dict(
prompts = prompts,
gpu = gpu,
num_steps = num_steps,
max_duration_in_seconds = max_duration_in_seconds,
num_inference_steps = num_inference_steps,
cfg_scale = cfg_scale,
do_loop = do_loop,
use_lerp_for_text = use_lerp_for_text,
seeds = seeds,
quality = quality,
eta = eta,
width = width,
height = height,
weights_path = weights_path,
scheduler=scheduler,
disable_tqdm = disable_tqdm,
beta_start = beta_start,
beta_end = beta_end,
beta_schedule = beta_schedule
),
indent=2,
sort_keys=False,
prompts = prompts,
gpu = gpu,
num_steps = num_steps,
max_duration_in_seconds = max_duration_in_seconds,
num_inference_steps = num_inference_steps,
cfg_scale = cfg_scale,
do_loop = do_loop,
use_lerp_for_text = use_lerp_for_text,
seeds = seeds,
quality = quality,
eta = eta,
width = width,
height = height,
weights_path = weights_path,
scheduler=scheduler,
disable_tqdm = disable_tqdm,
beta_start = beta_start,
beta_end = beta_end,
beta_schedule = beta_schedule
),
indent=2,
sort_keys=False,
))
#print(scheduler)
@ -1386,10 +1387,11 @@ def txt2vid(
#flaxddpms=flaxddpms_scheduler,
#flaxpndms=flaxpndms_scheduler,
)
with st.session_state["progress_bar_text"].container():
with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
load_diffusers_model(weights_path, torch_device)
with no_rerun:
with st.session_state["progress_bar_text"].container():
with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
load_diffusers_model(weights_path, torch_device)
if "pipe" not in server_state:
logger.error('wtf')
@ -1632,7 +1634,10 @@ def layout():
#prompt = st.text_area("Input Text","")
placeholder = "A corgi wearing a top hat as an oil painting."
prompt = st.text_area("Input Text","", placeholder=placeholder, height=54)
sygil_suggestions.suggestion_area(placeholder)
if "defaults" in st.session_state:
if st.session_state["defaults"].general.enable_suggestions:
sygil_suggestions.suggestion_area(placeholder)
if "defaults" in st.session_state:
if st.session_state['defaults'].admin.global_negative_prompt:
@ -1915,25 +1920,25 @@ def layout():
#print("Loading models")
# load the models when we hit the generate button for the first time, it wont be loaded after that so dont worry.
#load_models(False, st.session_state["use_GFPGAN"], True, st.session_state["RealESRGAN_model"])
with no_rerun:
if st.session_state["use_GFPGAN"]:
if "GFPGAN" in server_state:
logger.info("GFPGAN already loaded")
else:
with col2:
with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
# Load GFPGAN
if os.path.exists(st.session_state["defaults"].general.GFPGAN_dir):
try:
load_GFPGAN()
logger.info("Loaded GFPGAN")
except Exception:
import traceback
logger.error("Error loading GFPGAN:", file=sys.stderr)
logger.error(traceback.format_exc(), file=sys.stderr)
#with no_rerun:
if st.session_state["use_GFPGAN"]:
if "GFPGAN" in server_state:
logger.info("GFPGAN already loaded")
else:
if "GFPGAN" in server_state:
del server_state["GFPGAN"]
with col2:
with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
# Load GFPGAN
if os.path.exists(st.session_state["defaults"].general.GFPGAN_dir):
try:
load_GFPGAN()
logger.info("Loaded GFPGAN")
except Exception:
import traceback
logger.error("Error loading GFPGAN:", file=sys.stderr)
logger.error(traceback.format_exc(), file=sys.stderr)
else:
if "GFPGAN" in server_state:
del server_state["GFPGAN"]
#try:
# run video generation