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| from app_settings import AppSettings | |
| from utils import show_system_info | |
| import constants | |
| from argparse import ArgumentParser | |
| from context import Context | |
| from constants import APP_VERSION, LCM_DEFAULT_MODEL_OPENVINO | |
| from models.interface_types import InterfaceType | |
| from constants import DEVICE | |
| from state import get_settings | |
| import traceback | |
| from fastapi import FastAPI,Body | |
| import uvicorn | |
| import json | |
| import logging | |
| from PIL import Image | |
| import time | |
| from diffusers.utils import load_image | |
| import base64 | |
| import io | |
| from datetime import datetime | |
| from typing import Any | |
| from backend.models.lcmdiffusion_setting import DiffusionTask | |
| from frontend.utils import is_reshape_required | |
| from concurrent.futures import ThreadPoolExecutor | |
| context = Context(InterfaceType.WEBUI) | |
| previous_width = 0 | |
| previous_height = 0 | |
| previous_model_id = "" | |
| previous_num_of_images = 0 | |
| # parser = ArgumentParser(description=f"FAST SD CPU {constants.APP_VERSION}") | |
| # parser.add_argument( | |
| # "-s", | |
| # "--share", | |
| # action="store_true", | |
| # help="Create sharable link(Web UI)", | |
| # required=False, | |
| # ) | |
| # group = parser.add_mutually_exclusive_group(required=False) | |
| # group.add_argument( | |
| # "-g", | |
| # "--gui", | |
| # action="store_true", | |
| # help="Start desktop GUI", | |
| # ) | |
| # group.add_argument( | |
| # "-w", | |
| # "--webui", | |
| # action="store_true", | |
| # help="Start Web UI", | |
| # ) | |
| # group.add_argument( | |
| # "-r", | |
| # "--realtime", | |
| # action="store_true", | |
| # help="Start realtime inference UI(experimental)", | |
| # ) | |
| # group.add_argument( | |
| # "-v", | |
| # "--version", | |
| # action="store_true", | |
| # help="Version", | |
| # ) | |
| # parser.add_argument( | |
| # "--lcm_model_id", | |
| # type=str, | |
| # help="Model ID or path,Default SimianLuo/LCM_Dreamshaper_v7", | |
| # default="SimianLuo/LCM_Dreamshaper_v7", | |
| # ) | |
| # parser.add_argument( | |
| # "--prompt", | |
| # type=str, | |
| # help="Describe the image you want to generate", | |
| # ) | |
| # parser.add_argument( | |
| # "--image_height", | |
| # type=int, | |
| # help="Height of the image", | |
| # default=512, | |
| # ) | |
| # parser.add_argument( | |
| # "--image_width", | |
| # type=int, | |
| # help="Width of the image", | |
| # default=512, | |
| # ) | |
| # parser.add_argument( | |
| # "--inference_steps", | |
| # type=int, | |
| # help="Number of steps,default : 4", | |
| # default=4, | |
| # ) | |
| # parser.add_argument( | |
| # "--guidance_scale", | |
| # type=int, | |
| # help="Guidance scale,default : 1.0", | |
| # default=1.0, | |
| # ) | |
| # parser.add_argument( | |
| # "--number_of_images", | |
| # type=int, | |
| # help="Number of images to generate ,default : 1", | |
| # default=1, | |
| # ) | |
| # parser.add_argument( | |
| # "--seed", | |
| # type=int, | |
| # help="Seed,default : -1 (disabled) ", | |
| # default=-1, | |
| # ) | |
| # parser.add_argument( | |
| # "--use_openvino", | |
| # action="store_true", | |
| # help="Use OpenVINO model", | |
| # ) | |
| # parser.add_argument( | |
| # "--use_offline_model", | |
| # action="store_true", | |
| # help="Use offline model", | |
| # ) | |
| # parser.add_argument( | |
| # "--use_safety_checker", | |
| # action="store_false", | |
| # help="Use safety checker", | |
| # ) | |
| # parser.add_argument( | |
| # "--use_lcm_lora", | |
| # action="store_true", | |
| # help="Use LCM-LoRA", | |
| # ) | |
| # parser.add_argument( | |
| # "--base_model_id", | |
| # type=str, | |
| # help="LCM LoRA base model ID,Default Lykon/dreamshaper-8", | |
| # default="Lykon/dreamshaper-8", | |
| # ) | |
| # parser.add_argument( | |
| # "--lcm_lora_id", | |
| # type=str, | |
| # help="LCM LoRA model ID,Default latent-consistency/lcm-lora-sdv1-5", | |
| # default="latent-consistency/lcm-lora-sdv1-5", | |
| # ) | |
| # parser.add_argument( | |
| # "-i", | |
| # "--interactive", | |
| # action="store_true", | |
| # help="Interactive CLI mode", | |
| # ) | |
| # parser.add_argument( | |
| # "--use_tiny_auto_encoder", | |
| # action="store_true", | |
| # help="Use tiny auto encoder for SD (TAESD)", | |
| # ) | |
| # args = parser.parse_args() | |
| # if args.version: | |
| # print(APP_VERSION) | |
| # exit() | |
| # parser.print_help() | |
| show_system_info() | |
| print(f"Using device : {constants.DEVICE}") | |
| app_settings = get_settings() | |
| print(f"Found {len(app_settings.lcm_models)} LCM models in config/lcm-models.txt") | |
| print( | |
| f"Found {len(app_settings.stable_diffsuion_models)} stable diffusion models in config/stable-diffusion-models.txt" | |
| ) | |
| print( | |
| f"Found {len(app_settings.lcm_lora_models)} LCM-LoRA models in config/lcm-lora-models.txt" | |
| ) | |
| print( | |
| f"Found {len(app_settings.openvino_lcm_models)} OpenVINO LCM models in config/openvino-lcm-models.txt" | |
| ) | |
| app_settings.settings.lcm_diffusion_setting.use_openvino = True | |
| # from frontend.webui.ui import start_webui | |
| # print("Starting web UI mode") | |
| # start_webui( | |
| # args.share, | |
| # ) | |
| app = FastAPI(name="mutilParam") | |
| print("我执行了") | |
| def root(): | |
| return {"API": "hello"} | |
| async def predict(prompt=Body(...),imgbase64data=Body(...),negative_prompt=Body(None),userId=Body(None)): | |
| MAX_QUEUE_SIZE = 4 | |
| start = time.time() | |
| print("参数",imgbase64data,prompt) | |
| image_data = base64.b64decode(imgbase64data) | |
| image1 = Image.open(io.BytesIO(image_data)) | |
| w, h = image1.size | |
| newW = 512 | |
| newH = int(h * newW / w) | |
| img = image1.resize((newW, newH)) | |
| end1 = time.time() | |
| now = datetime.now() | |
| print(now) | |
| print("图像:", img.size) | |
| print("加载管道:", end1 - start) | |
| global previous_height, previous_width, previous_model_id, previous_num_of_images, app_settings | |
| app_settings.settings.lcm_diffusion_setting.prompt = prompt | |
| app_settings.settings.lcm_diffusion_setting.negative_prompt = negative_prompt | |
| app_settings.settings.lcm_diffusion_setting.init_image = image1 | |
| app_settings.settings.lcm_diffusion_setting.strength = 0.6 | |
| app_settings.settings.lcm_diffusion_setting.diffusion_task = ( | |
| DiffusionTask.image_to_image.value | |
| ) | |
| model_id = app_settings.settings.lcm_diffusion_setting.openvino_lcm_model_id | |
| reshape = False | |
| # app_settings.settings.lcm_diffusion_setting.image_height=newH | |
| image_width = app_settings.settings.lcm_diffusion_setting.image_width | |
| image_height = app_settings.settings.lcm_diffusion_setting.image_height | |
| num_images = app_settings.settings.lcm_diffusion_setting.number_of_images | |
| reshape = is_reshape_required( | |
| previous_width, | |
| image_width, | |
| previous_height, | |
| image_height, | |
| previous_model_id, | |
| model_id, | |
| previous_num_of_images, | |
| num_images, | |
| ) | |
| with ThreadPoolExecutor(max_workers=1) as executor: | |
| future = executor.submit( | |
| context.generate_text_to_image, | |
| app_settings.settings, | |
| reshape, | |
| DEVICE, | |
| ) | |
| images = future.result() | |
| previous_width = image_width | |
| previous_height = image_height | |
| previous_model_id = model_id | |
| previous_num_of_images = num_images | |
| output_image = images[0] | |
| end2 = time.time() | |
| print("测试",output_image) | |
| print("s生成完成:", end2 - end1) | |
| # 将图片对象转换为bytes | |
| image_data = io.BytesIO() | |
| # 将图像保存到BytesIO对象中，格式为JPEG | |
| output_image.save(image_data, format='JPEG') | |
| # 将BytesIO对象的内容转换为字节串 | |
| image_data_bytes = image_data.getvalue() | |
| output_image_base64 = base64.b64encode(image_data_bytes).decode('utf-8') | |
| print("完成的图片:", output_image_base64) | |
| return output_image_base64 | |
| async def predict(prompt=Body(...)): | |
| return f"您好,{prompt}" | |