mirror of
https://github.com/vladmandic/automatic
synced 2026-08-31 01:20:59 +02:00
Vladimir Mandic
76 lines
3.5 KiB
Python
76 lines
3.5 KiB
Python
from PIL import Image
|
|
from modules import shared, processing, images, sd_models
|
|
|
|
|
|
def get_tile(image: Image.Image, x: int, y: int, sx: int, sy: int) -> Image.Image:
|
|
return image.crop((
|
|
(x + 0) * image.width // sx,
|
|
(y + 0) * image.height // sy,
|
|
(x + 1) * image.width // sx,
|
|
(y + 1) * image.height // sy
|
|
))
|
|
|
|
|
|
def set_tile(image: Image.Image, x: int, y: int, tiled: Image.Image):
|
|
image.paste(tiled, (x * tiled.width, y * tiled.height))
|
|
return image
|
|
|
|
|
|
def run_tiling(p: processing.StableDiffusionProcessing, input_image: Image.Image) -> processing.Processed:
|
|
# prepare images
|
|
sx, sy = p.control_tile.split('x')
|
|
sx = int(sx)
|
|
sy = int(sy)
|
|
if sx <= 0 or sy <= 0:
|
|
raise ValueError('Control: invalid tile size')
|
|
control_image = p.task_args.get('control_image', None) or p.task_args.get('image', None)
|
|
control_upscaled = None
|
|
if isinstance(control_image, list) and len(control_image) > 0:
|
|
control_upscaled = images.resize_image(resize_mode=1 if sx==sy else 5,
|
|
im=control_image[0],
|
|
width=8 * int(sx * control_image[0].width) // 8,
|
|
height=8 * int(sy * control_image[0].height) // 8,
|
|
context='add with forward'
|
|
)
|
|
init_image = p.override or input_image
|
|
init_upscaled = None
|
|
if init_image is not None:
|
|
init_upscaled = images.resize_image(resize_mode=1 if sx==sy else 5,
|
|
im=init_image,
|
|
width=8 * int(sx * init_image.width) // 8,
|
|
height=8 * int(sy * init_image.height) // 8,
|
|
context='add with forward'
|
|
)
|
|
|
|
# stop processing from restoring pipeline on each iteration
|
|
orig_restore_pipeline = getattr(shared.sd_model, 'restore_pipeline', None)
|
|
shared.sd_model.restore_pipeline = None
|
|
|
|
# run tiling
|
|
for x in range(sx):
|
|
for y in range(sy):
|
|
shared.log.info(f'Control Tile: tile={x+1}-{sx}/{y+1}-{sy} target={control_upscaled}')
|
|
shared.sd_model = sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.IMAGE_2_IMAGE)
|
|
p.init_images = None
|
|
p.task_args['control_mode'] = p.control_mode
|
|
p.task_args['strength'] = p.denoising_strength
|
|
if init_upscaled is not None:
|
|
p.task_args['image'] = [get_tile(init_upscaled, x, y, sx, sy)]
|
|
if control_upscaled is not None:
|
|
p.task_args['control_image'] = [get_tile(control_upscaled, x, y, sx, sy)]
|
|
processed: processing.Processed = processing.process_images(p) # run actual pipeline
|
|
if processed is None or len(processed.images) == 0:
|
|
continue
|
|
control_upscaled = set_tile(control_upscaled, x, y, processed.images[0])
|
|
|
|
# post-process
|
|
p.width = control_upscaled.width
|
|
p.height = control_upscaled.height
|
|
processed.images = [control_upscaled]
|
|
processed.info = processed.infotext(p, 0)
|
|
processed.infotexts = [processed.info]
|
|
shared.sd_model.restore_pipeline = orig_restore_pipeline
|
|
if hasattr(shared.sd_model, 'restore_pipeline') and shared.sd_model.restore_pipeline is not None:
|
|
shared.sd_model.restore_pipeline()
|
|
return processed
|