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https://github.com/Sygil-Dev/sygil-webui.git
synced 2024-12-14 14:05:36 +03:00
Changed CFG scale to be a number_input instead of a slider.
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ZeroCool940711
parent
27c13fb625
commit
774073c8c3
@ -38,6 +38,7 @@ general:
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upscaling_method: "RealESRGAN"
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outdir_txt2img: outputs/txt2img
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outdir_img2img: outputs/img2img
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outdir_img2txt: outputs/img2txt
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gfpgan_cpu: False
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esrgan_cpu: False
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extra_models_cpu: False
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@ -83,7 +84,6 @@ txt2img:
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cfg_scale:
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value: 7.5
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min_value: 1.0
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max_value: 30.0
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step: 0.5
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seed: ""
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@ -148,7 +148,6 @@ txt2vid:
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cfg_scale:
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value: 7.5
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min_value: 1.0
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max_value: 30.0
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step: 0.5
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batch_count:
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@ -254,7 +253,6 @@ img2img:
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cfg_scale:
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value: 7.5
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min_value: 1.0
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max_value: 30.0
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step: 0.5
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batch_count:
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@ -277,9 +275,8 @@ img2img:
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find_noise_steps:
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value: 100
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min_value: 0
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max_value: 500
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step: 10
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min_value: 100
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step: 100
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LDSR_config:
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sampling_steps: 50
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@ -28,6 +28,7 @@ from omegaconf import OmegaConf
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# end of imports
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# ---------------------------------------------------------------------------------------------------------------
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def layout():
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st.header("Settings")
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@ -47,7 +48,6 @@ def layout():
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device_list.append(f"{id}: {name} ({human_readable_size(total_memory, decimal_places=0)})")
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with col1:
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st.title("General")
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st.session_state['defaults'].general.gpu = int(st.selectbox("GPU", device_list,
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@ -93,7 +93,8 @@ def layout():
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index=RealESRGAN_model_list.index(st.session_state['defaults'].general.RealESRGAN_model),
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help="Default RealESRGAN model. Default: 'RealESRGAN_x4plus'")
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Upscaler_list = ["RealESRGAN", "LDSR"]
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st.session_state['defaults'].general.upscaling_method = st.selectbox("Upscaler", Upscaler_list, index=Upscaler_list.index(st.session_state['defaults'].general.upscaling_method), help="Default upscaling method. Default: 'RealESRGAN'")
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st.session_state['defaults'].general.upscaling_method = st.selectbox("Upscaler", Upscaler_list, index=Upscaler_list.index(
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st.session_state['defaults'].general.upscaling_method), help="Default upscaling method. Default: 'RealESRGAN'")
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with col2:
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st.title("Performance")
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@ -202,8 +203,6 @@ def layout():
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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,
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help="Specify if we are running on app.Daisi.io . Default: False")
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with col4:
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st.title("Streamlit Config")
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@ -258,10 +257,6 @@ def layout():
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st.session_state["defaults"].txt2img.cfg_scale.min_value = st.number_input("Minimum CFG Scale Value", value=st.session_state['defaults'].txt2img.cfg_scale.min_value,
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help="Set the default minimum value for the CFG scale slider. Default is: 1")
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st.session_state["defaults"].txt2img.cfg_scale.max_value = st.number_input("Maximum CFG Scale Value",
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value=st.session_state['defaults'].txt2img.cfg_scale.max_value,
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help="Set the default maximum value for the CFG scale slider. Default is: 30")
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st.session_state["defaults"].txt2img.cfg_scale.step = st.number_input("CFG Slider Steps", value=st.session_state['defaults'].txt2img.cfg_scale.step,
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help="Set the default value for the number of steps on the CFG scale slider. Default is: 0.5")
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# Sampling Steps
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@ -291,7 +286,8 @@ def layout():
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default_sampler_list = ["k_lms", "k_euler", "k_euler_a", "k_dpm_2", "k_dpm_2_a", "k_heun", "PLMS", "DDIM"]
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st.session_state["defaults"].txt2img.default_sampler = st.selectbox("Default Sampler",
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default_sampler_list, index=default_sampler_list.index(st.session_state['defaults'].txt2img.default_sampler),
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default_sampler_list, index=default_sampler_list.index(
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st.session_state['defaults'].txt2img.default_sampler),
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help="Defaut sampler to use for txt2img. Default: k_euler")
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st.session_state['defaults'].txt2img.seed = st.text_input("Default Seed", value=st.session_state['defaults'].txt2img.seed, help="Default seed.")
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@ -321,7 +317,8 @@ def layout():
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st.session_state["defaults"].txt2img.write_info_files = st.checkbox("Write Info Files For Images", value=st.session_state['defaults'].txt2img.write_info_files,
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help="Choose to write the info files along with the generated images. Default: True")
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st.session_state["defaults"].txt2img.use_GFPGAN = st.checkbox("Use GFPGAN", value=st.session_state['defaults'].txt2img.use_GFPGAN, help="Choose to use GFPGAN. Default: False")
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st.session_state["defaults"].txt2img.use_GFPGAN = st.checkbox(
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"Use GFPGAN", value=st.session_state['defaults'].txt2img.use_GFPGAN, help="Choose to use GFPGAN. Default: False")
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st.session_state["defaults"].txt2img.use_upscaling = st.checkbox("Use Upscaling", value=st.session_state['defaults'].txt2img.use_upscaling,
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help="Choose to turn on upscaling by default. Default: False")
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@ -418,10 +415,6 @@ def layout():
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value=st.session_state['defaults'].img2img.cfg_scale.min_value,
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help="Set the default minimum value for the CFG scale slider. Default is: 1")
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st.session_state["defaults"].img2img.cfg_scale.max_value = st.number_input("Maximum Img2Img CFG Scale Value",
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value=st.session_state['defaults'].img2img.cfg_scale.max_value,
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help="Set the default maximum value for the CFG scale slider. Default is: 30")
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with col3:
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st.session_state["defaults"].img2img.cfg_scale.step = st.number_input("Img2Img CFG Slider Steps",
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value=st.session_state['defaults'].img2img.cfg_scale.step,
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@ -436,7 +429,6 @@ def layout():
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value=st.session_state['defaults'].img2img.sampling_steps.min_value,
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help="Set the default minimum value for the sampling steps slider. Default is: 1")
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st.session_state["defaults"].img2img.sampling_steps.step = st.number_input("Img2Img Sampling Slider Steps",
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value=st.session_state['defaults'].img2img.sampling_steps.step,
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help="Set the default value for the number of steps on the sampling steps slider. Default is: 10")
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@ -478,14 +470,10 @@ def layout():
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value=st.session_state['defaults'].img2img.find_noise_steps.min_value,
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help="Set the default minimum value for the find noise steps slider. Default is: 0")
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st.session_state["defaults"].img2img.find_noise_steps.max_value = st.number_input("Maximum Find Noise Steps",
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value=st.session_state['defaults'].img2img.find_noise_steps.max_value,
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help="Set the default maximum value for the find noise steps slider. Default is: 500")
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st.session_state["defaults"].img2img.find_noise_steps.step = st.number_input("Find Noise Slider Steps",
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value=st.session_state['defaults'].img2img.find_noise_steps.step,
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help="Set the default value for the number of steps on the find noise steps slider. \
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Default is: 10")
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Default is: 100")
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with col5:
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st.title("General Parameters")
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@ -522,7 +510,8 @@ def layout():
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value=st.session_state['defaults'].img2img.write_info_files,
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help="Choose to write the info files along with the generated images. Default: True")
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st.session_state["defaults"].img2img.use_GFPGAN = st.checkbox("Img2Img Use GFPGAN", value=st.session_state['defaults'].img2img.use_GFPGAN, help="Choose to use GFPGAN. Default: False")
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st.session_state["defaults"].img2img.use_GFPGAN = st.checkbox(
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"Img2Img Use GFPGAN", value=st.session_state['defaults'].img2img.use_GFPGAN, help="Choose to use GFPGAN. Default: False")
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st.session_state["defaults"].img2img.use_RealESRGAN = st.checkbox("Img2Img Use RealESRGAN", value=st.session_state['defaults'].img2img.use_RealESRGAN,
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help="Choose to use RealESRGAN. Default: False")
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@ -605,10 +594,6 @@ def layout():
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value=st.session_state['defaults'].txt2vid.cfg_scale.min_value,
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help="Set the default minimum value for the CFG scale slider. Default is: 1")
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st.session_state["defaults"].txt2vid.cfg_scale.max_value = st.number_input("Maximum txt2vid CFG Scale Value",
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value=st.session_state['defaults'].txt2vid.cfg_scale.max_value,
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help="Set the default maximum value for the CFG scale slider. Default is: 30")
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st.session_state["defaults"].txt2vid.cfg_scale.step = st.number_input("txt2vid CFG Slider Steps",
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value=st.session_state['defaults'].txt2vid.cfg_scale.step,
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help="Set the default value for the number of steps on the CFG scale slider. Default is: 0.5")
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@ -738,7 +723,6 @@ def layout():
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st.session_state['defaults'].txt2vid.variant_seed = st.text_input("Default txt2vid Variation Seed",
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value=st.session_state['defaults'].txt2vid.variant_seed, help="Default variation seed.")
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with col5:
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st.title("Beta Parameters")
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@ -405,9 +405,9 @@ def layout():
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value=st.session_state['defaults'].img2img.height.value, step=st.session_state['defaults'].img2img.height.step)
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seed = st.text_input("Seed:", value=st.session_state['defaults'].img2img.seed, help=" The seed to use, if left blank a random seed will be generated.")
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cfg_scale = st.slider("CFG (Classifier Free Guidance Scale):", min_value=st.session_state['defaults'].img2img.cfg_scale.min_value,
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max_value=st.session_state['defaults'].img2img.cfg_scale.max_value, value=st.session_state['defaults'].img2img.cfg_scale.value,
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step=st.session_state['defaults'].img2img.cfg_scale.step, help="How strongly the image should follow the prompt.")
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cfg_scale = st.number_input("CFG (Classifier Free Guidance Scale):", min_value=st.session_state['defaults'].img2img.cfg_scale.min_value,
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step=st.session_state['defaults'].img2img.cfg_scale.step,
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help="How strongly the image should follow the prompt.")
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st.session_state["denoising_strength"] = st.slider("Denoising Strength:", value=st.session_state['defaults'].img2img.denoising_strength.value,
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min_value=st.session_state['defaults'].img2img.denoising_strength.min_value,
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@ -431,8 +431,8 @@ def layout():
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help=""
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)
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noise_mode = noise_mode_list.index(noise_mode)
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find_noise_steps = st.slider("Find Noise Steps", value=st.session_state['defaults'].img2img.find_noise_steps.value,
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min_value=st.session_state['defaults'].img2img.find_noise_steps.min_value, max_value=st.session_state['defaults'].img2img.find_noise_steps.max_value,
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find_noise_steps = st.number_input("Find Noise Steps", value=st.session_state['defaults'].img2img.find_noise_steps.value,
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min_value=st.session_state['defaults'].img2img.find_noise_steps.min_value,
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step=st.session_state['defaults'].img2img.find_noise_steps.step)
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with st.expander("Batch Options"):
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@ -412,10 +412,10 @@ def layout():
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value=st.session_state['defaults'].txt2img.width.value, step=st.session_state['defaults'].txt2img.width.step)
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height = st.slider("Height:", min_value=st.session_state['defaults'].txt2img.height.min_value, max_value=st.session_state['defaults'].txt2img.height.max_value,
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value=st.session_state['defaults'].txt2img.height.value, step=st.session_state['defaults'].txt2img.height.step)
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cfg_scale = st.slider("CFG (Classifier Free Guidance Scale):", min_value=st.session_state['defaults'].txt2img.cfg_scale.min_value,
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max_value=st.session_state['defaults'].txt2img.cfg_scale.max_value,
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cfg_scale = st.number_input("CFG (Classifier Free Guidance Scale):", min_value=st.session_state['defaults'].txt2img.cfg_scale.min_value,
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value=st.session_state['defaults'].txt2img.cfg_scale.value, step=st.session_state['defaults'].txt2img.cfg_scale.step,
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help="How strongly the image should follow the prompt.")
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seed = st.text_input("Seed:", value=st.session_state['defaults'].txt2img.seed, help=" The seed to use, if left blank a random seed will be generated.")
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with st.expander("Batch Options"):
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@ -651,9 +651,10 @@ def layout():
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value=st.session_state['defaults'].txt2vid.width.value, step=st.session_state['defaults'].txt2vid.width.step)
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height = st.slider("Height:", min_value=st.session_state['defaults'].txt2vid.height.min_value, max_value=st.session_state['defaults'].txt2vid.height.max_value,
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value=st.session_state['defaults'].txt2vid.height.value, step=st.session_state['defaults'].txt2vid.height.step)
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cfg_scale = st.slider("CFG (Classifier Free Guidance Scale):", min_value=st.session_state['defaults'].txt2vid.cfg_scale.min_value,
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max_value=st.session_state['defaults'].txt2vid.cfg_scale.max_value, value=st.session_state['defaults'].txt2vid.cfg_scale.value,
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step=st.session_state['defaults'].txt2vid.cfg_scale.step, help="How strongly the image should follow the prompt.")
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cfg_scale = st.number_input("CFG (Classifier Free Guidance Scale):", min_value=st.session_state['defaults'].txt2vid.cfg_scale.min_value,
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value=st.session_state['defaults'].txt2vid.cfg_scale.value,
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step=st.session_state['defaults'].txt2vid.cfg_scale.step,
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help="How strongly the image should follow the prompt.")
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#uploaded_images = st.file_uploader("Upload Image", accept_multiple_files=False, type=["png", "jpg", "jpeg", "webp"],
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#help="Upload an image which will be used for the image to image generation.")
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