mirror of https://github.com/vladmandic/automatic
add detailer expert mode
Signed-off-by: Vladimir Mandic <mandic00@live.com>pull/4058/head
Vladimir Mandic
parent
287c3600d7
commit
a852d1cea9
10
CHANGELOG.md
10
CHANGELOG.md
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@ -1,8 +1,8 @@
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# Change Log for SD.Next
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## Update for 2025-07-20
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## Update for 2025-07-21
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### Highlights for 2025-07-20
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### Highlights for 2025-07-21
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Feature highlights include:
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- **ModernUI** layout redesign which should make it more user friendly and easier to navigate
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@ -26,7 +26,7 @@ Although upgrades and existing installations are tested and should work fine!
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[ReadMe](https://github.com/vladmandic/automatic/blob/master/README.md) | [ChangeLog](https://github.com/vladmandic/automatic/blob/master/CHANGELOG.md) | [Docs](https://vladmandic.github.io/sdnext-docs/) | [WiKi](https://github.com/vladmandic/automatic/wiki) | [Discord](https://discord.com/invite/sd-next-federal-batch-inspectors-1101998836328697867)
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### Details for 2025-07-20
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### Details for 2025-07-21
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- **License**
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- SD.Next [license](https://github.com/vladmandic/sdnext/blob/dev/LICENSE.txt) switched from **aGPL-v3.0** to **Apache-v2.0**
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@ -79,7 +79,7 @@ Although upgrades and existing installations are tested and should work fine!
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- new [Parameters](https://vladmandic.github.io/sdnext-docs/Parameters/) page that lists and explains all generation parameters
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massive thanks to @CalamitousFelicitousness for bringing this to life!
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- updated *Models, Video, LTX, FramePack, Styles*, etc.
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- **Compute**
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- **Compute**
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- support for [SageAttention2++](https://github.com/thu-ml/SageAttention)
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provides 10-15% performance improvement over default SDPA for transformer-based models!
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enable in *settings -> compute settings -> sdp options*
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@ -107,6 +107,8 @@ Although upgrades and existing installations are tested and should work fine!
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- **Batch** warn on unprocessable images and skip operations on errors so that other images can still be processed
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- **Metadata** improved parsing and detect foreign metadata
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detect ComfyUI images
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- **Detailer** add `expert` mode where list of detailer models can be converted to textbox for manual editing
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see [docs](https://vladmandic.github.io/sdnext-docs/Detailer/) for more information
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- **SDNQ**
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- use inference context during quantization
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- use static compile
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@ -1 +1 @@
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Subproject commit c12e8cda4e45a1d5f20659a30e329c7cc7e69339
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Subproject commit 716b1ee7dc8042ba2a62460425930cf3ab472919
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@ -5,7 +5,7 @@ from copy import copy
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import numpy as np
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import gradio as gr
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from PIL import Image, ImageDraw
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from modules import shared, processing, devices, processing_class, ui_common
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from modules import shared, processing, devices, processing_class, ui_common, ui_components, ui_symbols
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from modules.detailer import Detailer
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@ -46,6 +46,7 @@ class YoloRestorer(Detailer):
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super().__init__()
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self.models = {} # cache loaded models
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self.list = {}
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self.ui_mode = True
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self.enumerate()
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def name(self):
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@ -202,16 +203,28 @@ class YoloRestorer(Detailer):
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p.detailer_active = 0
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if np_image is None or p.detailer_active >= p.batch_size * p.n_iter:
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return np_image
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if len(shared.opts.detailer_models) == 0:
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models = [m.strip() for m in shared.opts.detailer_args.split(',')]
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if len(models) == 0:
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models = shared.opts.detailer_models
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if len(models) == 0:
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shared.log.warning('Detailer: model=None')
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return np_image
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models_used = []
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shared.log.debug(f'Detailer: models={models}')
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# create backups
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orig_apply_overlay = shared.opts.mask_apply_overlay
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orig_p = p.__dict__.copy()
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orig_cls = p.__class__
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models_used = []
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for i, model_val in enumerate(models):
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if ':' in model_val:
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model_name, model_args = model_val.split(':', 1)
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else:
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model_name, model_args = model_val, ''
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model_args = [m.strip() for m in model_args.split(':')]
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model_args = {k.strip(): v.strip() for k, v in (arg.split('=') for arg in model_args if '=' in arg)}
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for i, model_name in enumerate(shared.opts.detailer_models):
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name, model = self.load(model_name)
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if model is None:
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shared.log.warning(f'Detailer: model="{name}" not loaded')
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@ -267,6 +280,7 @@ class YoloRestorer(Detailer):
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'height': resolution,
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'vae_type': orig_p.get('vae_type', 'Full'),
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}
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args.update(model_args)
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if args['denoising_strength'] == 0:
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shared.log.debug(f'Detailer: model="{name}" strength=0 skip')
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return np_image
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@ -286,7 +300,7 @@ class YoloRestorer(Detailer):
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p.steps = orig_p.get('steps', 0)
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report = [{'label': i.label, 'score': i.score, 'size': f'{i.width}x{i.height}' } for i in items]
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shared.log.info(f'Detailer: model="{name}" items={report} args={items[0].args} strength={p.detailer_strength} blur={p.mask_blur} width={p.width} height={p.height} padding={p.inpaint_full_res_padding}')
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shared.log.info(f'Detailer: model="{name}" items={report} args={args}')
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models_used.append(name)
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mask_all = []
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@ -338,9 +352,19 @@ class YoloRestorer(Detailer):
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return np_image
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def change_mode(self, dropdown, text):
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self.ui_mode = not self.ui_mode
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if self.ui_mode:
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value = [val.split(':')[0].strip() for val in text.split(',')]
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return gr.update(visible=True, value=value), gr.update(visible=False), gr.update(visible=True)
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else:
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value = ', '.join(dropdown)
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return gr.update(visible=False), gr.update(visible=True, value=value), gr.update(visible=False)
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def ui(self, tab: str):
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def ui_settings_change(detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end):
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def ui_settings_change(detailers, text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end):
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shared.opts.detailer_models = detailers
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shared.opts.detailer_args = text if not self.ui_mode else ''
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shared.opts.detailer_classes = classes
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shared.opts.detailer_padding = padding
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shared.opts.detailer_blur = blur
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@ -358,8 +382,11 @@ class YoloRestorer(Detailer):
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with gr.Row():
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enabled = gr.Checkbox(label="Enable detailer pass", elem_id=f"{tab}_detailer_enabled", value=False)
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with gr.Row():
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detailers = gr.Dropdown(label="Detailer models", elem_id=f"{tab}_detailers", choices=self.list, value=shared.opts.detailer_models, multiselect=True)
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ui_common.create_refresh_button(detailers, self.enumerate, {}, elem_id=f"{tab}_detailers_refresh")
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detailers = gr.Dropdown(label="Detailer models", elem_id=f"{tab}_detailers", choices=self.list, value=shared.opts.detailer_models, multiselect=True, visible=True)
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detailers_text = gr.Textbox(label="Detailer models", elem_id=f"{tab}_detailers_text", placeholder="Comma separated list of detailer models", lines=2, visible=False, interactive=True)
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refresh_btn = ui_common.create_refresh_button(detailers, self.enumerate, {}, elem_id=f"{tab}_detailers_refresh")
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ui_mode = ui_components.ToolButton(value=ui_symbols.view)
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ui_mode.click(fn=self.change_mode, inputs=[detailers, detailers_text], outputs=[detailers, detailers_text, refresh_btn])
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with gr.Row():
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classes = gr.Textbox(label="Detailer classes", placeholder="Classes", elem_id=f"{tab}_detailer_classes")
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with gr.Row():
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@ -385,15 +412,16 @@ class YoloRestorer(Detailer):
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with gr.Row(elem_classes=['flex-break']):
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renoise_value = gr.Slider(minimum=0.5, maximum=1.5, step=0.01, label='Renoise', value=shared.opts.detailer_sigma_adjust, elem_id=f"{tab}_detailer_renoise")
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renoise_end = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Renoise end', value=shared.opts.detailer_sigma_adjust_max, elem_id=f"{tab}_detailer_renoise_end")
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detailers.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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classes.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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padding.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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blur.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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min_confidence.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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max_detected.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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min_size.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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max_size.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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iou.change(fn=ui_settings_change, inputs=[detailers, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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detailers.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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detailers_text.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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classes.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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padding.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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blur.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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min_confidence.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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max_detected.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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min_size.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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max_size.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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iou.change(fn=ui_settings_change, inputs=[detailers, detailers_text, classes, strength, padding, blur, min_confidence, max_detected, min_size, max_size, iou, steps, renoise_value, renoise_end], outputs=[])
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return enabled, prompt, negative, steps, strength
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@ -582,5 +582,9 @@ def switch_class(p: StableDiffusionProcessing, new_class: type, dct: dict = None
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if dct is not None: # post init set additional values
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for k, v in dct.items():
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if hasattr(p, k):
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setattr(p, k, v)
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valtype = type(getattr(p, k, None))
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if valtype in [int, float, str]:
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setattr(p, k, valtype(v))
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else:
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setattr(p, k, v)
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return p
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@ -141,7 +141,7 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts=None, all_seeds=No
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args['Resize name mask'] = p.resize_name_mask
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args['Resize scale mask'] = p.scale_by_mask
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if 'detailer' in p.ops:
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args["Detailer"] = ', '.join(shared.opts.detailer_models)
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args["Detailer"] = ', '.join(shared.opts.detailer_models) if len(shared.opts.detailer_args) == 0 else shared.opts.detailer_args
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args["Detailer steps"] = p.detailer_steps
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args["Detailer strength"] = p.detailer_strength
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args["Detailer prompt"] = p.detailer_prompt if len(p.detailer_prompt) > 0 else None
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@ -623,6 +623,7 @@ options_templates.update(options_section(('postprocessing', "Postprocessing"), {
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"detailer_padding": OptionInfo(20, "Item padding", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1, "visible": False}),
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"detailer_blur": OptionInfo(10, "Item edge blur", gr.Slider, {"minimum": 0, "maximum": 100, "step": 1, "visible": False}),
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"detailer_models": OptionInfo(['face-yolo8n'], "Detailer models", gr.Dropdown, lambda: {"multiselect":True, "choices": list(yolo.list), "visible": False}),
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"detailer_args": OptionInfo("", "Detailer args", gr.Textbox, { "visible": False}),
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"detailer_unload": OptionInfo(False, "Move detailer model to CPU when complete"),
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"detailer_augment": OptionInfo(True, "Detailer use model augment"),
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@ -19,6 +19,7 @@
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"venv": ". venv/bin/activate",
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"start": ". venv/bin/activate; python launch.py --debug",
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"localize": "node cli/localize.js",
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"update": ". venv/bin/activate && pip install --upgrade transformers accelerate huggingface_hub safetensors tokenizers peft compel pytorch_lightning",
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"eslint": "eslint . javascript/ extensions-builtin/sdnext-modernui/javascript/",
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"ruff": ". venv/bin/activate && ruff check",
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"pylint": ". venv/bin/activate && pylint *.py modules/ pipelines/ scripts/ extensions-builtin/ | grep -v '^*'",
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@ -263,7 +263,6 @@ axis_options = [
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AxisOption("[Control] Strength", float, apply_control('control_strength')),
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AxisOption("[Control] Start", float, apply_control('control_start')),
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AxisOption("[Control] End", float, apply_control('control_end')),
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AxisOption("[HiDiffusion] T1", float, apply_override('hidiffusion_t1')),
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AxisOption("[HiDiffusion] T2", float, apply_override('hidiffusion_t2')),
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AxisOption("[HiDiffusion] Agression step", float, apply_field('hidiffusion_steps')),
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