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import time
import math
import logging
from PIL import Image, ImageDraw, ImageFilter
from backend.models.lcmdiffusion_setting import DiffusionTask
from context import Context
from constants import DEVICE
def generate_upscaled_image(
config,
input_path=None,
strength=0.3,
scale_factor=2.0,
tile_overlap=16,
upscale_settings=None,
context: Context = None,
output_path=None,
image_format="PNG",
):
if config == None or (
input_path == None or input_path == "" and upscale_settings == None
):
logging.error("Wrong arguments in tiled upscale function call!")
return
# Use the upscale_settings dict if provided; otherwise, build the
# upscale_settings dict using the function arguments and default values
if upscale_settings == None:
upscale_settings = {
"source_file": input_path,
"target_file": None,
"output_format": image_format,
"strength": strength,
"scale_factor": scale_factor,
"prompt": config.lcm_diffusion_setting.prompt,
"tile_overlap": tile_overlap,
"tile_size": 256,
"tiles": [],
}
source_image = Image.open(input_path) # PIL image
else:
source_image = Image.open(upscale_settings["source_file"])
upscale_settings["source_image"] = source_image
if upscale_settings["target_file"]:
result = Image.open(upscale_settings["target_file"])
else:
result = Image.new(
mode="RGBA",
size=(
source_image.size[0] * int(upscale_settings["scale_factor"]),
source_image.size[1] * int(upscale_settings["scale_factor"]),
),
color=(0, 0, 0, 0),
)
upscale_settings["target_image"] = result
# If the custom tile definition array 'tiles' is empty, proceed with the
# default tiled upscale task by defining all the possible image tiles; note
# that the actual tile size is 'tile_size' + 'tile_overlap' and the target
# image width and height are no longer constrained to multiples of 256 but
# are instead multiples of the actual tile size
if len(upscale_settings["tiles"]) == 0:
tile_size = upscale_settings["tile_size"]
scale_factor = upscale_settings["scale_factor"]
tile_overlap = upscale_settings["tile_overlap"]
total_cols = math.ceil(
source_image.size[0] / tile_size
) # Image width / tile size
total_rows = math.ceil(
source_image.size[1] / tile_size
) # Image height / tile size
for y in range(0, total_rows):
y_offset = tile_overlap if y > 0 else 0 # Tile mask offset
for x in range(0, total_cols):
x_offset = tile_overlap if x > 0 else 0 # Tile mask offset
x1 = x * tile_size
y1 = y * tile_size
w = tile_size + (tile_overlap if x < total_cols - 1 else 0)
h = tile_size + (tile_overlap if y < total_rows - 1 else 0)
mask_box = ( # Default tile mask box definition
x_offset,
y_offset,
int(w * scale_factor),
int(h * scale_factor),
)
upscale_settings["tiles"].append(
{
"x": x1,
"y": y1,
"w": w,
"h": h,
"mask_box": mask_box,
"prompt": upscale_settings["prompt"], # Use top level prompt if available
"scale_factor": scale_factor,
}
)
# Generate the output image tiles
for i in range(0, len(upscale_settings["tiles"])):
generate_upscaled_tile(
config,
i,
upscale_settings,
context=context,
)
# Save completed upscaled image
if upscale_settings["output_format"].upper() == "JPEG":
result_rgb = result.convert("RGB")
result.close()
result = result_rgb
result.save(output_path)
result.close()
source_image.close()
return
def get_current_tile(
config,
context,
strength,
):
config.lcm_diffusion_setting.strength = strength
config.lcm_diffusion_setting.diffusion_task = DiffusionTask.image_to_image.value
if (
config.lcm_diffusion_setting.use_tiny_auto_encoder
and config.lcm_diffusion_setting.use_openvino
):
config.lcm_diffusion_setting.use_tiny_auto_encoder = False
current_tile = context.generate_text_to_image(
settings=config,
reshape=True,
device=DEVICE,
save_images=False,
save_config=False,
)[0]
return current_tile
# Generates a single tile from the source image as defined in the
# upscale_settings["tiles"] array with the corresponding index and pastes the
# generated tile into the target image using the corresponding mask and scale
# factor; note that scale factor for the target image and the individual tiles
# can be different, this function will adjust scale factors as needed
def generate_upscaled_tile(
config,
index,
upscale_settings,
context: Context = None,
):
if config == None or upscale_settings == None:
logging.error("Wrong arguments in tile creation function call!")
return
x = upscale_settings["tiles"][index]["x"]
y = upscale_settings["tiles"][index]["y"]
w = upscale_settings["tiles"][index]["w"]
h = upscale_settings["tiles"][index]["h"]
tile_prompt = upscale_settings["tiles"][index]["prompt"]
scale_factor = upscale_settings["scale_factor"]
tile_scale_factor = upscale_settings["tiles"][index]["scale_factor"]
target_width = int(w * tile_scale_factor)
target_height = int(h * tile_scale_factor)
strength = upscale_settings["strength"]
source_image = upscale_settings["source_image"]
target_image = upscale_settings["target_image"]
mask_image = generate_tile_mask(config, index, upscale_settings)
config.lcm_diffusion_setting.number_of_images = 1
config.lcm_diffusion_setting.prompt = tile_prompt
config.lcm_diffusion_setting.image_width = target_width
config.lcm_diffusion_setting.image_height = target_height
config.lcm_diffusion_setting.init_image = source_image.crop((x, y, x + w, y + h))
current_tile = None
print(f"[SD Upscale] Generating tile {index + 1}/{len(upscale_settings['tiles'])} ")
if tile_prompt == None or tile_prompt == "":
config.lcm_diffusion_setting.prompt = ""
config.lcm_diffusion_setting.negative_prompt = ""
current_tile = get_current_tile(config, context, strength)
else:
# Attempt to use img2img with low denoising strength to
# generate the tiles with the extra aid of a prompt
# context = get_context(InterfaceType.CLI)
current_tile = get_current_tile(config, context, strength)
if math.isclose(scale_factor, tile_scale_factor):
target_image.paste(
current_tile, (int(x * scale_factor), int(y * scale_factor)), mask_image
)
else:
target_image.paste(
current_tile.resize((int(w * scale_factor), int(h * scale_factor))),
(int(x * scale_factor), int(y * scale_factor)),
mask_image.resize((int(w * scale_factor), int(h * scale_factor))),
)
mask_image.close()
current_tile.close()
config.lcm_diffusion_setting.init_image.close()
# Generate tile mask using the box definition in the upscale_settings["tiles"]
# array with the corresponding index; note that tile masks for the default
# tiled upscale task can be reused but that would complicate the code, so
# new tile masks are instead created for each tile
def generate_tile_mask(
config,
index,
upscale_settings,
):
scale_factor = upscale_settings["scale_factor"]
tile_overlap = upscale_settings["tile_overlap"]
tile_scale_factor = upscale_settings["tiles"][index]["scale_factor"]
w = int(upscale_settings["tiles"][index]["w"] * tile_scale_factor)
h = int(upscale_settings["tiles"][index]["h"] * tile_scale_factor)
# The Stable Diffusion pipeline automatically adjusts the output size
# to multiples of 8 pixels; the mask must be created with the same
# size as the output tile
w = w - (w % 8)
h = h - (h % 8)
mask_box = upscale_settings["tiles"][index]["mask_box"]
if mask_box == None:
# Build a default solid mask with soft/transparent edges
mask_box = (
tile_overlap,
tile_overlap,
w - tile_overlap,
h - tile_overlap,
)
mask_image = Image.new(mode="RGBA", size=(w, h), color=(0, 0, 0, 0))
mask_draw = ImageDraw.Draw(mask_image)
mask_draw.rectangle(tuple(mask_box), fill=(0, 0, 0))
mask_blur = mask_image.filter(ImageFilter.BoxBlur(tile_overlap - 1))
mask_image.close()
return mask_blur
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