292 lines
12 KiB
Python
292 lines
12 KiB
Python
from modules.sd_samplers_kdiffusion import KDiffusionSampler
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import modules.scripts as scripts
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from modules import shared
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import gradio as gr
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import random
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from scripts.cc_noise import *
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from scripts.cc_xyz import xyz_support
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from scripts.cc_scaling import apply_scaling
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from scripts.cc_version import VERSION
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from scripts.cc_version import clean_outdated
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from scripts.cc_colorpicker import create_colorpicker
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from scripts.cc_colorpicker import horizontal_js
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from scripts.cc_colorpicker import vertical_js
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from scripts.cc_style import StyleManager
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style_manager = StyleManager()
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style_manager.load_styles()
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og_callback = KDiffusionSampler.callback_state
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class VectorscopeCC(scripts.Script):
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def __init__(self):
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clean_outdated('cc.py')
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self.xyzCache = {}
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xyz_support(self.xyzCache)
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def title(self):
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return "Vectorscope CC"
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def show(self, is_img2img):
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return scripts.AlwaysVisible
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def ui(self, is_img2img):
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with gr.Accordion(f"Vectorscope CC {VERSION}", elem_id='vec-cc-' + ('img' if is_img2img else 'txt'), open=False):
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with gr.Row():
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enable = gr.Checkbox(label="Enable")
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latent = gr.Checkbox(label="Alt.")
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early = gr.Slider(label="Skip", minimum=0.0, maximum=1.0, step=0.1, value=0.0)
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with gr.Row():
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bri = gr.Slider(label="Brightness", minimum=-6.0, maximum=6.0, step=0.1, value=0.0)
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con = gr.Slider(label="Contrast", minimum=-2.5, maximum=2.5, step=0.05, value=0.0)
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sat = gr.Slider(label="Saturation", minimum=0.25, maximum=1.75, step=0.05, value=1.0)
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with gr.Row():
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with gr.Column():
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r = gr.Slider(label="R", info='Cyan | Red', minimum=-3.0, maximum=3.0, step=0.05, value=0.0, elem_id='cc-r-' + ('img' if is_img2img else 'txt'))
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g = gr.Slider(label="G", info='Magenta | Green',minimum=-3.0, maximum=3.0, step=0.05, value=0.0, elem_id='cc-g-' + ('img' if is_img2img else 'txt'))
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b = gr.Slider(label="B", info='Yellow | Blue',minimum=-3.0, maximum=3.0, step=0.05, value=0.0, elem_id='cc-b-' + ('img' if is_img2img else 'txt'))
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create_colorpicker(is_img2img)
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for component in [r, g, b]:
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component.change(None, inputs=[r, g, b], outputs=[], _js=horizontal_js(is_img2img))
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component.change(None, inputs=[r, g, b], outputs=[], _js=vertical_js(is_img2img))
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with gr.Accordion("Styles", open=False):
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with gr.Row():
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style_choice = gr.Dropdown(label="Styles", choices=style_manager.list_style(), scale = 3)
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apply_btn = gr.Button(value="Apply Style", elem_id='cc-apply-' + ('img' if is_img2img else 'txt'), scale = 2)
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refresh_btn = gr.Button(value="Refresh Style", scale = 2)
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with gr.Row():
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style_name = gr.Textbox(label="Style Name", scale = 3)
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save_btn = gr.Button(value="Save Style", elem_id='cc-save-' + ('img' if is_img2img else 'txt'), scale = 2)
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delete_btn = gr.Button(value="Delete Style", scale = 2)
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apply_btn.click(fn=style_manager.get_style, inputs=style_choice, outputs=[latent, bri, con, sat, r, g, b])
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save_btn.click(fn=lambda *args: gr.update(choices=style_manager.save_style(*args)), inputs=[style_name, latent, bri, con, sat, r, g, b], outputs=style_choice)
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delete_btn.click(fn=lambda name: gr.update(choices=style_manager.delete_style(name)), inputs=style_name, outputs=style_choice)
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refresh_btn.click(fn=lambda _: gr.update(choices=style_manager.list_style()), outputs=style_choice)
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with gr.Accordion("Advanced Settings", open=False):
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doHR = gr.Checkbox(label="Process Hires. fix")
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method = gr.Radio(["Straight", "Straight Abs.", "Cross", "Cross Abs.", "Ones", "N.Random", "U.Random", "Multi-Res", "Multi-Res Abs."], label="Noise Settings", value="Straight Abs.")
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scaling = gr.Radio(["Flat", "Cos", "Sin", "1 - Cos", "1 - Sin"], label="Scaling Settings", value="Flat")
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with gr.Row():
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reset_btn = gr.Button(value="Reset")
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self.register_reset(reset_btn, enable, latent, bri, con, sat, early, r, g, b, doHR, method, scaling)
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random_btn = gr.Button(value="Randomize")
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self.register_random(random_btn, bri, con, sat, r, g, b)
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return [enable, latent, bri, con, sat, early, r, g, b, doHR, method, scaling]
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def register_reset(self, reset_btn, enable, latent, bri, con, sat, early, r, g, b, doHR, method, scaling):
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for component in [enable, latent, doHR]:
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reset_btn.click(fn=lambda _: gr.update(value=False), outputs=component)
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for component in [early, bri, con, r, g, b]:
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reset_btn.click(fn=lambda _: gr.update(value=0.0), outputs=component)
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for component in [sat]:
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reset_btn.click(fn=lambda _: gr.update(value=1.0), outputs=component)
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reset_btn.click(fn=lambda _: gr.update(value='Straight Abs.'), outputs=method)
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reset_btn.click(fn=lambda _: gr.update(value='Flat'), outputs=scaling)
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def register_random(self, random_btn, bri, con, sat, r, g, b):
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for component in [bri, con, r, g, b]:
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random_btn.click(fn=lambda _: gr.update(value=round(random.uniform(-2.5, 2.5), 2)), outputs=component)
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for component in [sat]:
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random_btn.click(fn=lambda _: gr.update(value=round(random.uniform(0.5, 1.5), 2)), outputs=component)
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def parse_bool(self, string:str):
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if string.lower() == "true":
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return True
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if string.lower() == "false":
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return False
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raise ValueError(f"Invalid Value: {string}")
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def process(self, p, enable:bool, latent:bool, bri:float, con:float, sat:float, early:float, r:float, g:float, b:float, doHR:bool, method:str, scaling:str):
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if 'Enable' in self.xyzCache.keys():
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enable = self.parse_bool(self.xyzCache['Enable'])
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if not enable:
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if 'Enable' not in self.xyzCache.keys():
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if len(self.xyzCache) > 0:
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print('\n[X/Y/Z Plot] x [Vec.CC] Extension is not Enabled!\n')
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self.xyzCache.clear()
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KDiffusionSampler.callback_state = og_callback
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return p
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if 'Random' in self.xyzCache.keys():
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if len(self.xyzCache) > 1:
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print('\n[X/Y/Z Plot] x [Vec.CC] Randomize is Enabled!\nSome settings will not apply!\n')
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else:
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print('\n[X/Y/Z Plot] x [Vec.CC] Randomize is Enabled!\n')
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cc_seed = None
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for k, v in self.xyzCache.items():
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match k:
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case 'Alt':
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latent = self.parse_bool(v)
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case 'Brightness':
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bri = v
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case 'Contrast':
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con = v
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case 'Saturation':
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sat = v
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case 'Skip':
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early = v
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case 'R':
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r = v
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case 'G':
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g = v
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case 'B':
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b = v
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case 'DoHR':
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doHR = self.parse_bool(v)
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case 'Method':
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method = v
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case 'Scaling':
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scaling = v
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case 'Random':
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cc_seed = v
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self.xyzCache.clear()
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if method == 'Disabled':
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KDiffusionSampler.callback_state = og_callback
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return p
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steps = p.steps
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if not hasattr(p, 'enable_hr') and hasattr(p, 'denoising_strength') and not shared.opts.img2img_fix_steps:
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steps = int(steps * p.denoising_strength)
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stop = steps * (1.0 - early)
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if cc_seed is not None:
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random.seed(cc_seed)
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bri = round(random.uniform(-3.0, 3.0), 2)
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r = round(random.uniform(-3.0, 3.0), 2)
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g = round(random.uniform(-3.0, 3.0), 2)
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b = round(random.uniform(-3.0, 3.0), 2)
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con = round(random.uniform(0.25, 1.75), 2)
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sat = round(random.uniform(0.25, 1.75), 2)
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print(f'-> Seed: {cc_seed}')
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print(f'Brightness:\t{bri}')
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print(f'Contrast:\t{con}')
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print(f'Saturation:\t{sat}')
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print(f'R:\t\t{r}')
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print(f'G:\t\t{g}')
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print(f'B:\t\t{b}\n')
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if stop < 1:
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return p
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if hasattr(shared.opts, 'cc_metadata') and shared.opts.cc_metadata is True:
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cc_params = f'Alt: {latent}, Skip: {early}, Brightness: {bri}, Contrast: {con}, Saturation: {sat}, RGB: ({r}, {g}, {b}), Noise: {method}, Proc. Hr.F: {doHR}, Scaling: {scaling}'
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p.extra_generation_params.update({f'Vec. CC [{VERSION}]': cc_params})
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bri /= steps
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con /= steps
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sat = pow(sat, 1.0 / steps)
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r /= steps
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g /= steps
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b /= steps
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mode = 'x' if latent else 'denoised'
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# Channel 0: Dark | Bright
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# Channel 1: Purple | Green
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# Channel 2: Red | Cyan
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# Channel 2: Violet | Yellow
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def callback_state(self, d):
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if not doHR:
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if hasattr(p, 'enable_hr') and p.enable_hr:
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if not hasattr(p, 'hr_pass'):
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p.hr_pass = 0
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if p.hr_pass == 0:
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if d["i"] == 0:
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p.hr_pass = 1
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elif p.hr_pass == 1:
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if d["i"] == 0:
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p.hr_pass = 2
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if p.hr_pass == 2:
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return og_callback(self, d)
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if d["i"] > stop:
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return og_callback(self, d)
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source = d[mode]
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# "Straight", "Straight Abs.", "Cross", "Cross Abs.", "Ones", "N.Random", "U.Random", "Multi-Res", "Multi-Res Abs."
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if 'Straight' in method:
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target = d[mode]
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elif 'Cross' in method:
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cross = 'x' if mode == 'denoised' else 'denoised'
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target = d[cross]
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elif 'Multi-Res' in method:
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target = multires_noise(d[mode], 'Abs' in method)
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elif method == 'Ones':
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target = ones(d[mode])
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elif method == 'N.Random':
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target = normal_noise(d[mode])
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elif method == 'U.Random':
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target = gaussian_noise(d[mode])
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if 'Abs' in method:
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target = to_abs(target)
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batchSize = d[mode].size(0)
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mods = apply_scaling(scaling, d["i"], steps, bri, con, sat, r, g, b)
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for i in range(batchSize):
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BRIGHTNESS = [source[i, 0], target[i, 0]]
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R = [source[i, 2], target[i, 2]]
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G = [source[i, 1], target[i, 1]]
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B = [source[i, 3], target[i, 3]]
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BRIGHTNESS[0] += BRIGHTNESS[1] * mods[0]
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BRIGHTNESS[0] += get_delta(BRIGHTNESS[0]) * mods[1]
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R[0] -= R[1] * mods[3]
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G[0] += G[1] * mods[4]
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B[0] -= B[1] * mods[5]
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R[0] *= mods[2]
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G[0] *= mods[2]
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B[0] *= mods[2]
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return og_callback(self, d)
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KDiffusionSampler.callback_state = callback_state
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return p
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def postprocess_image(self, p, *args):
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if hasattr(p, 'hr_pass'):
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del p.hr_pass
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def postprocess(self, p, processed, *args):
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KDiffusionSampler.callback_state = og_callback
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