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https://github.com/Sygil-Dev/sygil-webui.git
synced 2024-12-15 06:21:34 +03:00
Changed CFG scale to be a number_input instead of a slider.
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@ -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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1156
scripts/Settings.py
1156
scripts/Settings.py
File diff suppressed because it is too large
Load Diff
@ -405,23 +405,23 @@ 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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max_value=st.session_state['defaults'].img2img.denoising_strength.max_value,
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step=st.session_state['defaults'].img2img.denoising_strength.step)
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min_value=st.session_state['defaults'].img2img.denoising_strength.min_value,
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max_value=st.session_state['defaults'].img2img.denoising_strength.max_value,
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step=st.session_state['defaults'].img2img.denoising_strength.step)
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mask_expander = st.empty()
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with mask_expander.expander("Mask"):
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mask_mode_list = ["Mask", "Inverted mask", "Image alpha"]
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mask_mode = st.selectbox("Mask Mode", mask_mode_list,
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help="Select how you want your image to be masked.\"Mask\" modifies the image where the mask is white.\n\
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\"Inverted mask\" modifies the image where the mask is black. \"Image alpha\" modifies the image where the image is transparent."
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)
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help="Select how you want your image to be masked.\"Mask\" modifies the image where the mask is white.\n\
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\"Inverted mask\" modifies the image where the mask is black. \"Image alpha\" modifies the image where the image is transparent."
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)
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mask_mode = mask_mode_list.index(mask_mode)
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@ -431,26 +431,26 @@ 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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st.session_state["batch_count"] = st.number_input("Batch count.", value=st.session_state['defaults'].img2img.batch_count.value,
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help="How many iterations or batches of images to generate in total.")
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help="How many iterations or batches of images to generate in total.")
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st.session_state["batch_size"] = st.number_input("Batch size", value=st.session_state.defaults.img2img.batch_size.value,
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help="How many images are at once in a batch.\
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It increases the VRAM usage a lot but if you have enough VRAM it can reduce the time it takes to finish generation as more images are generated at once.\
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Default: 1")
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help="How many images are at once in a batch.\
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It increases the VRAM usage a lot but if you have enough VRAM it can reduce the time it takes to finish generation as more images are generated at once.\
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Default: 1")
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with st.expander("Preview Settings"):
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st.session_state["update_preview"] = st.session_state["defaults"].general.update_preview
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st.session_state["update_preview_frequency"] = st.number_input("Update Image Preview Frequency",
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min_value=1,
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value=st.session_state['defaults'].img2img.update_preview_frequency,
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help="Frequency in steps at which the the preview image is updated. By default the frequency \
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is set to 1 step.")
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min_value=1,
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value=st.session_state['defaults'].img2img.update_preview_frequency,
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help="Frequency in steps at which the the preview image is updated. By default the frequency \
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is set to 1 step.")
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#
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with st.expander("Advanced"):
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with st.expander("Output Settings"):
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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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