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loopback moved to scripts, added support for multiple batches, changed to honor save grids and how grids in web setting

This commit is contained in:
AUTOMATIC 2022-09-14 14:47:54 +03:00
parent c253d6bdab
commit c9430e53f6
4 changed files with 86 additions and 50 deletions
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43
modules/img2img.py
View File

@ -11,10 +11,9 @@ from modules.ui import plaintext_to_html
import modules.images as images
import modules.scripts
def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init_img_with_mask, init_mask, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, denoising_strength_change_factor: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init_img_with_mask, init_mask, mask_mode, steps: int, sampler_index: int, mask_blur: int, inpainting_fill: int, restore_faces: bool, tiling: bool, mode: int, n_iter: int, batch_size: int, cfg_scale: float, denoising_strength: float, seed: int, subseed: int, subseed_strength: float, seed_resize_from_h: int, seed_resize_from_w: int, height: int, width: int, resize_mode: int, upscaler_index: str, upscale_overlap: int, inpaint_full_res: bool, inpainting_mask_invert: int, *args):
is_inpaint = mode == 1
is_loopback = mode == 2
is_upscale = mode == 3
is_upscale = mode == 2
if is_inpaint:
if mask_mode == 0:
@ -61,46 +60,10 @@ def img2img(prompt: str, negative_prompt: str, prompt_style: str, init_img, init
denoising_strength=denoising_strength,
inpaint_full_res=inpaint_full_res,
inpainting_mask_invert=inpainting_mask_invert,
extra_generation_params={
"Denoising strength change factor": (denoising_strength_change_factor if is_loopback else None)
}
)
print(f"\nimg2img: {prompt}", file=shared.progress_print_out)
if is_loopback:
output_images, info = None, None
history = []
initial_seed = None
initial_info = None
state.job_count = n_iter
for i in range(n_iter):
p.n_iter = 1
p.batch_size = 1
p.do_not_save_grid = True
state.job = f"Batch {i + 1} out of {n_iter}"
processed = process_images(p)
if initial_seed is None:
initial_seed = processed.seed
initial_info = processed.info
init_img = processed.images[0]
p.init_images = [init_img]
p.seed = processed.seed + 1
p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
history.append(processed.images[0])
grid = images.image_grid(history, batch_size, rows=1)
images.save_image(grid, p.outpath_grids, "grid", initial_seed, prompt, opts.grid_format, info=info, short_filename=not opts.grid_extended_filename, grid=True, p=p)
processed = Processed(p, history, initial_seed, initial_info)
elif is_upscale:
if is_upscale:
initial_info = None
processing.fix_seed(p)

11
modules/ui.py
View File

@ -387,7 +387,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
with gr.Row().style(equal_height=False):
with gr.Column(variant='panel'):
with gr.Group():
switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'Loopback', 'SD upscale'], value='Redraw whole image', type="index", show_label=False)
switch_mode = gr.Radio(label='Mode', elem_id="img2img_mode", choices=['Redraw whole image', 'Inpaint a part of image', 'SD upscale'], value='Redraw whole image', type="index", show_label=False)
init_img = gr.Image(label="Image for img2img", source="upload", interactive=True, type="pil")
init_img_with_mask = gr.Image(label="Image for inpainting with mask", elem_id="img2maskimg", source="upload", interactive=True, type="pil", tool="sketch", visible=False, image_mode="RGBA")
init_mask = gr.Image(label="Mask", source="upload", interactive=True, type="pil", visible=False)
@ -421,7 +421,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
with gr.Group():
cfg_scale = gr.Slider(minimum=1.0, maximum=30.0, step=0.5, label='CFG Scale', value=7.0)
denoising_strength = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label='Denoising strength', value=0.75)
denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1, visible=False)
with gr.Group():
width = gr.Slider(minimum=64, maximum=2048, step=64, label="Width", value=512)
@ -455,8 +454,7 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
def apply_mode(mode, uploadmask):
is_classic = mode == 0
is_inpaint = mode == 1
is_loopback = mode == 2
is_upscale = mode == 3
is_upscale = mode == 2
return {
init_img: gr_show(not is_inpaint or (is_inpaint and uploadmask == 1)),
@ -466,12 +464,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
mask_mode: gr_show(is_inpaint),
mask_blur: gr_show(is_inpaint),
inpainting_fill: gr_show(is_inpaint),
batch_size: gr_show(not is_loopback),
sd_upscale_upscaler_name: gr_show(is_upscale),
sd_upscale_overlap: gr_show(is_upscale),
inpaint_full_res: gr_show(is_inpaint),
inpainting_mask_invert: gr_show(is_inpaint),
denoising_strength_change_factor: gr_show(is_loopback),
img2img_interrogate: gr_show(not is_inpaint),
}
@ -486,12 +482,10 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
mask_mode,
mask_blur,
inpainting_fill,
batch_size,
sd_upscale_upscaler_name,
sd_upscale_overlap,
inpaint_full_res,
inpainting_mask_invert,
denoising_strength_change_factor,
img2img_interrogate,
]
)
@ -532,7 +526,6 @@ def create_ui(txt2img, img2img, run_extras, run_pnginfo):
batch_size,
cfg_scale,
denoising_strength,
denoising_strength_change_factor,
seed,
subseed, subseed_strength, seed_resize_from_h, seed_resize_from_w,
height,

4
script.js
View File

@ -13,7 +13,6 @@ titles = {
"Seed": "A value that determines the output of random number generator - if you create an image with same parameters and seed as another image, you'll get the same result",
"Inpaint a part of image": "Draw a mask over an image, and the script will regenerate the masked area with content according to prompt",
"Loopback": "Process an image, use it as an input, repeat. Batch count determins number of iterations.",
"SD upscale": "Upscale image normally, split result into tiles, improve each tile using img2img, merge whole image back",
"Just resize": "Resize image to target resolution. Unless height and width match, you will get incorrect aspect ratio.",
@ -58,6 +57,9 @@ titles = {
"Images filename pattern": "Use following tags to define how filenames for images are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
"Directory name pattern": "Use following tags to define how subdirectories for images and grids are chosen: [steps], [cfg], [prompt], [prompt_spaces], [width], [height], [sampler], [seed], [model_hash], [prompt_words], [date]; leave empty for default.",
"Loopback": "Process an image, use it as an input, repeat.",
"Loops": "How many times to repeat processing an image and using it as input for the next iteration",
}
function gradioApp(){

78
scripts/loopback.py Normal file
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@ -0,0 +1,78 @@
import numpy as np
from tqdm import trange
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
class Script(scripts.Script):
def title(self):
return "Loopback"
def show(self, is_img2img):
return is_img2img
def ui(self, is_img2img):
loops = gr.Slider(minimum=1, maximum=32, step=1, label='Loops', value=4)
denoising_strength_change_factor = gr.Slider(minimum=0.9, maximum=1.1, step=0.01, label='Denoising strength change factor', value=1)
return [loops, denoising_strength_change_factor]
def run(self, p, loops, denoising_strength_change_factor):
processing.fix_seed(p)
batch_count = p.n_iter
p.extra_generation_params = {
"Denoising strength change factor": denoising_strength_change_factor,
}
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
for n in range(batch_count):
history = []
for i in range(loops):
p.n_iter = 1
p.batch_size = 1
p.do_not_save_grid = True
state.job = f"Iteration {i + 1}/{loops}, batch {n + 1}/{batch_count}"
processed = processing.process_images(p)
if initial_seed is None:
initial_seed = processed.seed
initial_info = processed.info
init_img = processed.images[0]
p.init_images = [init_img]
p.seed = processed.seed + 1
p.denoising_strength = min(max(p.denoising_strength * denoising_strength_change_factor, 0.1), 1)
history.append(processed.images[0])
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