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Fixed the generate button needing to be clicked twice on the first run as the models would cause a rerun stopping the generation from starting right away and needing a second click on the generate button. (#1704)
This commit is contained in:
Alejandro Gil
GitHub
commit
d90c44c197
@ -29,7 +29,7 @@ streamlit==1.14.0
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streamlit-on-Hover-tabs==1.0.1
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streamlit-option-menu==0.3.2
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streamlit_nested_layout==0.1.1
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streamlit-server-state==0.14.2
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streamlit-server-state==0.15.0
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streamlit-tensorboard==0.0.2
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streamlit-elements==0.1.* # used for the draggable dashboard and new UI design (WIP)
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streamlit-ace==0.1.1 # used to replace the text area on the prompt and also for the code editor tool.
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@ -14,7 +14,7 @@
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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# base webui import and utils.
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from sd_utils import st, server_state, \
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from sd_utils import st, server_state, no_rerun, \
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generation_callback, process_images, KDiffusionSampler, \
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custom_models_available, RealESRGAN_available, GFPGAN_available, \
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LDSR_available, load_models, hc, seed_to_int, logger, \
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@ -694,11 +694,12 @@ def layout():
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#print("Loading models")
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# load the models when we hit the generate button for the first time, it wont be loaded after that so dont worry.
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with col3_img2img_layout:
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with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
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load_models(use_LDSR=st.session_state["use_LDSR"], LDSR_model=st.session_state["LDSR_model"],
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use_GFPGAN=st.session_state["use_GFPGAN"], GFPGAN_model=st.session_state["GFPGAN_model"] ,
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use_RealESRGAN=st.session_state["use_RealESRGAN"], RealESRGAN_model=st.session_state["RealESRGAN_model"],
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CustomModel_available=server_state["CustomModel_available"], custom_model=st.session_state["custom_model"])
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with no_rerun:
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with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
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load_models(use_LDSR=st.session_state["use_LDSR"], LDSR_model=st.session_state["LDSR_model"],
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use_GFPGAN=st.session_state["use_GFPGAN"], GFPGAN_model=st.session_state["GFPGAN_model"] ,
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use_RealESRGAN=st.session_state["use_RealESRGAN"], RealESRGAN_model=st.session_state["RealESRGAN_model"],
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CustomModel_available=server_state["CustomModel_available"], custom_model=st.session_state["custom_model"])
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if uploaded_images:
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#image = Image.fromarray(image).convert('RGBA')
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@ -22,7 +22,7 @@ from streamlit.runtime.scriptrunner import StopException
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#from streamlit.runtime.scriptrunner import script_run_context
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#streamlit components section
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from streamlit_server_state import server_state, server_state_lock
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from streamlit_server_state import server_state, server_state_lock, no_rerun
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import hydralit_components as hc
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from hydralit import HydraHeadApp
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import streamlit_nested_layout
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@ -14,7 +14,7 @@
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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# base webui import and utils.
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from sd_utils import st, MemUsageMonitor, server_state, \
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from sd_utils import st, MemUsageMonitor, server_state, no_rerun, \
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get_next_sequence_number, check_prompt_length, torch_gc, \
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save_sample, generation_callback, process_images, \
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KDiffusionSampler, \
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@ -431,7 +431,7 @@ def layout():
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if st.session_state['defaults'].admin.global_negative_prompt:
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prompt += f"### {st.session_state['defaults'].admin.global_negative_prompt}"
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print(prompt)
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#print(prompt)
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# creating the page layout using columns
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col1, col2, col3 = st.columns([2,5,2], gap="large")
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@ -658,12 +658,13 @@ def layout():
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if generate_button:
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with col2:
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if not use_stable_horde:
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with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
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load_models(use_LDSR=st.session_state["use_LDSR"], LDSR_model=st.session_state["LDSR_model"],
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use_GFPGAN=st.session_state["use_GFPGAN"], GFPGAN_model=st.session_state["GFPGAN_model"] ,
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use_RealESRGAN=st.session_state["use_RealESRGAN"], RealESRGAN_model=st.session_state["RealESRGAN_model"],
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CustomModel_available=server_state["CustomModel_available"], custom_model=st.session_state["custom_model"])
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with no_rerun:
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if not use_stable_horde:
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with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
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load_models(use_LDSR=st.session_state["use_LDSR"], LDSR_model=st.session_state["LDSR_model"],
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use_GFPGAN=st.session_state["use_GFPGAN"], GFPGAN_model=st.session_state["GFPGAN_model"] ,
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use_RealESRGAN=st.session_state["use_RealESRGAN"], RealESRGAN_model=st.session_state["RealESRGAN_model"],
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CustomModel_available=server_state["CustomModel_available"], custom_model=st.session_state["custom_model"])
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#print(st.session_state['use_RealESRGAN'])
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#print(st.session_state['use_LDSR'])
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@ -21,7 +21,7 @@ https://github.com/nateraw/stable-diffusion-videos
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repo and the original gist script from
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https://gist.github.com/karpathy/00103b0037c5aaea32fe1da1af553355
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"""
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from sd_utils import st, MemUsageMonitor, server_state, torch_gc, \
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from sd_utils import st, MemUsageMonitor, server_state, no_rerun, torch_gc, \
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custom_models_available, RealESRGAN_available, GFPGAN_available, \
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LDSR_available, hc, seed_to_int, logger, slerp, optimize_update_preview_frequency, \
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load_learned_embed_in_clip, load_GFPGAN, RealESRGANModel
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@ -1909,25 +1909,25 @@ def layout():
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#print("Loading models")
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# load the models when we hit the generate button for the first time, it wont be loaded after that so dont worry.
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#load_models(False, st.session_state["use_GFPGAN"], True, st.session_state["RealESRGAN_model"])
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if st.session_state["use_GFPGAN"]:
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if "GFPGAN" in server_state:
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logger.info("GFPGAN already loaded")
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with no_rerun:
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if st.session_state["use_GFPGAN"]:
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if "GFPGAN" in server_state:
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logger.info("GFPGAN already loaded")
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else:
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with col2:
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with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
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# Load GFPGAN
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if os.path.exists(st.session_state["defaults"].general.GFPGAN_dir):
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try:
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load_GFPGAN()
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logger.info("Loaded GFPGAN")
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except Exception:
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import traceback
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logger.error("Error loading GFPGAN:", file=sys.stderr)
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logger.error(traceback.format_exc(), file=sys.stderr)
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else:
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with col2:
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with hc.HyLoader('Loading Models...', hc.Loaders.standard_loaders,index=[0]):
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# Load GFPGAN
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if os.path.exists(st.session_state["defaults"].general.GFPGAN_dir):
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try:
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load_GFPGAN()
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logger.info("Loaded GFPGAN")
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except Exception:
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import traceback
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logger.error("Error loading GFPGAN:", file=sys.stderr)
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logger.error(traceback.format_exc(), file=sys.stderr)
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else:
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if "GFPGAN" in server_state:
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del server_state["GFPGAN"]
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if "GFPGAN" in server_state:
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del server_state["GFPGAN"]
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#try:
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# run video generation
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