stable-diffusion-webui/scripts/poor_mans_outpainting.py
AUTOMATIC a243bc7859 added progressbar
added an option to disable progressbar
added interrupt support to DDIM/PLMS
2022-09-06 02:09:01 +03:00

115 lines
4.3 KiB
Python

import math
import modules.scripts as scripts
import gradio as gr
from PIL import Image, ImageDraw
from modules import images, processing
from modules.processing import Processed, process_images
from modules.shared import opts, cmd_opts, state
class Script(scripts.Script):
def title(self):
return "Poor man's outpainting"
def show(self, is_img2img):
return is_img2img
def ui(self, is_img2img):
if not is_img2img:
return None
pixels = gr.Slider(label="Pixels to expand", minimum=8, maximum=128, step=8)
mask_blur = gr.Slider(label='Mask blur', minimum=0, maximum=64, step=1, value=4, visible=False)
inpainting_fill = gr.Radio(label='Masked content', choices=['fill', 'original', 'latent noise', 'latent nothing'], value='fill', type="index", visible=False)
return [pixels, mask_blur, inpainting_fill]
def run(self, p, pixels, mask_blur, inpainting_fill):
initial_seed = None
initial_info = None
p.mask_blur = mask_blur
p.inpainting_fill = inpainting_fill
p.inpaint_full_res = False
init_img = p.init_images[0]
target_w = math.ceil((init_img.width + pixels * 2) / 64) * 64
target_h = math.ceil((init_img.height + pixels * 2) / 64) * 64
border_x = (target_w - init_img.width)//2
border_y = (target_h - init_img.height)//2
img = Image.new("RGB", (target_w, target_h))
img.paste(init_img, (border_x, border_y))
mask = Image.new("L", (img.width, img.height), "white")
draw = ImageDraw.Draw(mask)
draw.rectangle((border_x + mask_blur * 2, border_y + mask_blur * 2, mask.width - border_x - mask_blur * 2, mask.height - border_y - mask_blur * 2), fill="black")
latent_mask = Image.new("L", (img.width, img.height), "white")
latent_draw = ImageDraw.Draw(latent_mask)
latent_draw.rectangle((border_x + 1, border_y + 1, mask.width - border_x - 1, mask.height - border_y - 1), fill="black")
processing.torch_gc()
grid = images.split_grid(img, tile_w=p.width, tile_h=p.height, overlap=pixels)
grid_mask = images.split_grid(mask, tile_w=p.width, tile_h=p.height, overlap=pixels)
grid_latent_mask = images.split_grid(mask, tile_w=p.width, tile_h=p.height, overlap=pixels)
p.n_iter = 1
p.batch_size = 1
p.do_not_save_grid = True
p.do_not_save_samples = True
work = []
work_mask = []
work_latent_mask = []
work_results = []
for (_, _, row), (_, _, row_mask), (_, _, row_latent_mask) in zip(grid.tiles, grid_mask.tiles, grid_latent_mask.tiles):
for tiledata, tiledata_mask, tiledata_latent_mask in zip(row, row_mask, row_latent_mask):
work.append(tiledata[2])
work_mask.append(tiledata_mask[2])
work_latent_mask.append(tiledata_latent_mask[2])
batch_count = len(work)
print(f"Poor man's outpainting will process a total of {len(work)} images tiled as {len(grid.tiles[0][2])}x{len(grid.tiles)}.")
state.job_count = batch_count
for i in range(batch_count):
p.init_images = [work[i]]
p.image_mask = work_mask[i]
p.latent_mask = work_latent_mask[i]
state.job = f"Batch {i + 1} out of {batch_count}"
processed = process_images(p)
if initial_seed is None:
initial_seed = processed.seed
initial_info = processed.info
p.seed = processed.seed + 1
work_results += processed.images
state.nextjob()
image_index = 0
for y, h, row in grid.tiles:
for tiledata in row:
tiledata[2] = work_results[image_index] if image_index < len(work_results) else Image.new("RGB", (p.width, p.height))
image_index += 1
combined_image = images.combine_grid(grid)
if opts.samples_save:
images.save_image(combined_image, p.outpath_samples, "", initial_seed, p.prompt, opts.grid_format, info=initial_info)
processed = Processed(p, [combined_image], initial_seed, initial_info)
return processed