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from typing import Any
from app_settings import Settings
from models.interface_types import InterfaceType
from backend.models.lcmdiffusion_setting import DiffusionTask
from backend.lcm_text_to_image import LCMTextToImage
from time import perf_counter
from backend.image_saver import ImageSaver
from pprint import pprint
class Context:
def __init__(
self,
interface_type: InterfaceType,
device="cpu",
):
self.interface_type = interface_type.value
self.lcm_text_to_image = LCMTextToImage(device)
self._latency = 0
@property
def latency(self):
return self._latency
def generate_text_to_image(
self,
settings: Settings,
reshape: bool = False,
device: str = "cpu",
save_images=True,
save_config=True,
) -> Any:
if (
settings.lcm_diffusion_setting.use_tiny_auto_encoder
and settings.lcm_diffusion_setting.use_openvino
):
print(
"WARNING: Tiny AutoEncoder is not supported in Image to image mode (OpenVINO)"
)
tick = perf_counter()
from state import get_settings
if (
settings.lcm_diffusion_setting.diffusion_task
== DiffusionTask.text_to_image.value
):
settings.lcm_diffusion_setting.init_image = None
if save_config:
get_settings().save()
pprint(settings.lcm_diffusion_setting.model_dump())
if not settings.lcm_diffusion_setting.lcm_lora:
return None
self.lcm_text_to_image.init(
device,
settings.lcm_diffusion_setting,
)
images = self.lcm_text_to_image.generate(
settings.lcm_diffusion_setting,
reshape,
)
elapsed = perf_counter() - tick
if save_images and settings.generated_images.save_image:
ImageSaver.save_images(
settings.generated_images.path,
images=images,
lcm_diffusion_setting=settings.lcm_diffusion_setting,
format=settings.generated_images.format,
)
self._latency = elapsed
print(f"Latency : {elapsed:.2f} seconds")
if settings.lcm_diffusion_setting.controlnet:
if settings.lcm_diffusion_setting.controlnet.enabled:
images.append(settings.lcm_diffusion_setting.controlnet._control_image)
return images
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