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import numpy as np
from tqdm import trange
from PIL import Image, ImageEnhance
import modules.scripts as scripts
import gradio as gr
from modules import processing, shared, sd_samplers, images
from modules.processing import Processed
from modules.sd_samplers import samplers
from modules.shared import opts, cmd_opts, state
from math import sin, pi
class Script(scripts.Script):
def title(self):
return "Advanced loopback"
def show(self, is_img2img):
return is_img2img
def ui(self, is_img2img):
loops = gr.Number(minimum=1, step=1, label='Loops', value=4)
use_first_image_colors = gr.Checkbox(label='Use first image colors (custom color correction) ', value=False)
denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor (overridden if proportional used)', value=1)
zoom_level = gr.Slider(minimum=1, maximum=1.1, step=0.001, label='Zoom level', value=1)
with gr.Row():
direction_x = gr.Slider(minimum=-0.1, maximum=0.1, step=0.01, label='Direction X', value=0)
direction_y = gr.Slider(minimum=-0.1, maximum=0.1, step=0.01, label='Direction Y', value=0)
with gr.Row():
denoising_strength_first_image = gr.Number(minimum=0, step=1, label='Denoising strength start ', value=0)
denoising_strength_last_image = gr.Number(minimum=0, step=1, label='Denoising strength end ', value=4)
denoising_strength_min = gr.Slider(minimum=0.1, maximum=1, step=0.01, label='Denoising strength proportional change starting value ', value=0.1)
denoising_strength_max = gr.Slider(minimum=0.1, maximum=1, step=0.01, label='Denoising strength proportional change ending value (0.1 = disabled) ', value=0.1)
cfg_scale_min = gr.Slider(minimum=0.1, maximum=30, step=0.1, label='CFG scale proportional change starting value ', value=0.1)
cfg_scale_max = gr.Slider(minimum=0.1, maximum=30, step=0.1, label='CFG scale proportional change ending value (0.1 = disabled) ', value=0.1)
saturation_per_image = gr.Slider(minimum=0.99, maximum=1.01, step=0.001, label='Saturation enhancement per image ', value=1)
with gr.Row():
use_sine_variation_dns = gr.Checkbox(label='Use sine denoising strength variation (CFG will be scaled with it if the slider is > 0.1)', value=True)
phase_diff_denoising = gr.Slider(minimum=0, maximum=1, step=0.05, label='Phase difference', value=0)
amplify_sine_variation_denoise = gr.Slider(minimum=1, maximum=10, step=1, label='Denoising strength exponentiation ', value=1)
with gr.Row():
use_sine_variation_zoom = gr.Checkbox(label='Use sine zoom variation', value=False)
phase_diff_zoom = gr.Slider(minimum=0, maximum=1, step=0.05, label='Phase difference', value=0)
amplify_sine_variation_zoom = gr.Slider(minimum=1, maximum=10, step=1, label='Zoom exponentiation ', value=1)
with gr.Row():
use_multi_prompts = gr.Checkbox(label='Use multiple prompts', value=False)
same_seed_per_prompt = gr.Checkbox(label='Same seed per prompt', value=False)
same_seed_always = gr.Checkbox(label='Same seed for everything', value=False)
same_init_image = gr.Checkbox(label='Original init image for everything', value=False)
multi_prompts = gr.Textbox(label="Multiple prompts : 1 line positive, 1 line negative, leave a blank line for no negative", lines=2, max_lines=2000)
return [
loops,
denoising_strength_change_factor,
zoom_level,
direction_x,
direction_y,
denoising_strength_first_image,
denoising_strength_last_image,
denoising_strength_min,
denoising_strength_max,
cfg_scale_min,
cfg_scale_max,
saturation_per_image,
use_first_image_colors,
use_sine_variation_dns,
use_sine_variation_zoom,
phase_diff_zoom,
use_multi_prompts,
multi_prompts,
amplify_sine_variation_zoom,
same_seed_per_prompt,
phase_diff_denoising,
amplify_sine_variation_denoise,
same_seed_always,
same_init_image
]
def zoom_into(self, img, zoom, direction_x, direction_y):
neg = lambda x: 1 if x > 0 else -1
if abs(direction_x) > zoom-1 : direction_x = (zoom-1)*neg(direction_x)*0.999999999999999 #*0.999999999999999 to avoid a float rounding error that makes it higher than desired
if abs(direction_y) > zoom-1 : direction_y = (zoom-1)*neg(direction_y)*0.999999999999999
w, h = img.size
x = w/2+direction_x*w/4
y = h/2-direction_y*h/4
zoom2 = zoom * 2
img = img.crop((x - w / zoom2, y - h / zoom2,
x + w / zoom2, y + h / zoom2))
return img.resize((w, h), Image.LANCZOS)
def run(self, p,
loops,
denoising_strength_change_factor,
zoom_level,
direction_x,
direction_y,
denoising_strength_first_image,
denoising_strength_last_image,
denoising_strength_min,
denoising_strength_max,
cfg_scale_min,
cfg_scale_max,
saturation_per_image,
use_first_image_colors,
use_sine_variation_dns,
use_sine_variation_zoom,
phase_diff_zoom,
use_multi_prompts,
multi_prompts,
amplify_sine_variation_zoom,
same_seed_per_prompt,
phase_diff_denoising,
amplify_sine_variation_denoise,
same_seed_always,
same_init_image
):
ppos = []
pneg = []
if use_multi_prompts :
prompts_list = multi_prompts.splitlines()
oddeven = lambda x: 1 if x%2==0 else 0
for x in range(len(prompts_list)) :
if oddeven(x):
ppos.append(prompts_list[x])
else:
pneg.append(prompts_list[x])
if len(pneg) < len(ppos) :
pneg.append("")
def remap_range(value, minIn, MaxIn, minOut, maxOut):
if value > MaxIn: value = MaxIn;
if value < minIn: value = minIn;
finalValue = ((value - minIn) / (MaxIn - minIn)) * (maxOut - minOut) + minOut;
return finalValue;
def get_sin_steps(i,amplify,phase_diff=0):
i -= denoising_strength_first_image
range = (denoising_strength_last_image - denoising_strength_first_image)
x = i % (range)
y = remap_range(x,0,range,0,1)
y = y ** amplify
z = sin((y+phase_diff/2)*pi)
return z
processing.fix_seed(p)
batch_count = p.n_iter
p.extra_generation_params = {
"Denoising strength change factor": denoising_strength_change_factor,
'Denoising strength proportional change start image':denoising_strength_first_image,
'Denoising strength proportional change end image':denoising_strength_last_image,
'Denoising strength proportional change starting value':denoising_strength_min,
'Denoising strength proportional change ending value':denoising_strength_max,
'CFG min':cfg_scale_min,
'CFG max':cfg_scale_max,
'use first image colors': use_first_image_colors,
'Saturation enhancement per image':saturation_per_image,
'Zoom level':zoom_level,
}
p.batch_size = 1
p.n_iter = 1
output_images, info = None, None
initial_seed = None
initial_info = None
grids = []
all_images = []
state.job_count = loops * batch_count
original_image = p.init_images[0].copy()
if opts.img2img_color_correction:
p.color_corrections = [processing.setup_color_correction(p.init_images[0])]
for n in range(batch_count):
history = []
multi_prompts_index = 0
loops = round(loops)
for i in range(loops):
p.n_iter = 1
p.batch_size = 1
p.do_not_save_grid = True
if use_multi_prompts :
image_range = (denoising_strength_last_image - denoising_strength_first_image)
il = i % (image_range)
if i == 0:
p.prompt = ppos[multi_prompts_index]
p.negative_prompt = pneg[multi_prompts_index]
print("Prompt :",p.prompt)
print("Negative prompt :",p.negative_prompt)
if il == 0 and i > 0:
multi_prompts_index+=1
try:
if same_seed_per_prompt:
if not same_seed_always:
p.subseed = p.subseed + 1 if p.subseed_strength > 0 else p.subseed
p.seed = p.seed + 1 if p.subseed_strength == 0 else p.seed
p.prompt = ppos[multi_prompts_index]
p.negative_prompt = pneg[multi_prompts_index]
except Exception as e:
multi_prompts_index = 0
if same_seed_per_prompt:
if not same_seed_always:
p.subseed = p.subseed + 1 if p.subseed_strength > 0 else p.subseed
p.seed = p.seed + 1 if p.subseed_strength == 0 else p.seed
p.prompt = ppos[multi_prompts_index]
p.negative_prompt = pneg[multi_prompts_index]
# print("Prompt :",p.prompt)
# print("Negative prompt :",p.negative_prompt)
if use_first_image_colors:
p.color_corrections = [processing.setup_color_correction(original_image)]
state.job = f"Iteration {i + 1}/{loops}, batch {n + 1}/{batch_count}"
if denoising_strength_max > 0.1 :
if use_sine_variation_dns :
ds = remap_range(get_sin_steps(i,amplify_sine_variation_denoise,phase_diff_denoising),0,1,denoising_strength_min,denoising_strength_max)
else:
ds = remap_range(i+1,denoising_strength_first_image,denoising_strength_last_image,denoising_strength_min,denoising_strength_max)
p.denoising_strength = round(ds,3)
print("Denoising strength : "+str(p.denoising_strength))
if cfg_scale_max > 0.1 :
if use_sine_variation_dns :
cfgs = remap_range(get_sin_steps(i,amplify_sine_variation_denoise,phase_diff_denoising),0,1,cfg_scale_min,cfg_scale_max)
else:
cfgs = remap_range(i+1,denoising_strength_first_image,denoising_strength_last_image,cfg_scale_min,cfg_scale_max)
p.cfg_scale = round(cfgs,2)
print("CFG scale : "+str(p.cfg_scale))
processed = processing.process_images(p)
if zoom_level != 1:
if use_sine_variation_zoom :
if loops >= denoising_strength_first_image :
z = remap_range(get_sin_steps(i,amplify_sine_variation_zoom,phase_diff_zoom),0,1,1,zoom_level)
processed.images[0] = self.zoom_into(processed.images[0], z, direction_x, direction_y)
print("Zoom level :",z)
else:
processed.images[0] = self.zoom_into(processed.images[0], zoom_level, direction_x, direction_y)
if initial_seed is None:
initial_seed = processed.seed
initial_info = processed.info
if not same_init_image :
init_img = processed.images[0]
else:
init_img = original_image
if saturation_per_image != 1 :
init_img = ImageEnhance.Color(init_img).enhance(saturation_per_image)
p.init_images = [init_img]
if not same_seed_per_prompt:
if not same_seed_always:
p.subseed = p.subseed + 1 if p.subseed_strength > 0 else p.subseed
p.seed = p.seed + 1 if p.subseed_strength == 0 else p.seed
p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
history.append(processed.images[0])
if state.interrupted:
break
grid = images.image_grid(history, rows=1)
if opts.grid_save:
images.save_image(grid, p.outpath_grids, "grid", initial_seed, p.prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
grids.append(grid)
all_images += history
if opts.return_grid:
all_images = grids + all_images
processed = Processed(p, all_images, initial_seed, initial_info)
return processed
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