| import json |
| import os |
| import subprocess |
| import sys |
| from datetime import datetime |
| from threading import Lock |
|
|
| import starlette.responses as starlette_responses |
| from fastapi import BackgroundTasks, FastAPI, Request |
| from fastapi.responses import FileResponse |
| from fastapi.staticfiles import StaticFiles |
|
|
| import toml |
|
|
| from mikazuki.models import TaggerInterrogateRequest |
| from mikazuki.tagger.interrogator import WaifuDiffusionInterrogator, on_interrogate |
|
|
| app = FastAPI() |
| lock = Lock() |
| interrogator = WaifuDiffusionInterrogator('wd14-convnextv2-v2', repo_id='SmilingWolf/wd-v1-4-convnextv2-tagger-v2', revision='v2.0') |
|
|
| |
| _origin_guess_type = starlette_responses.guess_type |
|
|
|
|
| def _hooked_guess_type(*args, **kwargs): |
| url = args[0] |
| r = _origin_guess_type(*args, **kwargs) |
| if url.endswith(".js"): |
| r = ("application/javascript", None) |
| elif url.endswith(".css"): |
| r = ("text/css", None) |
| return r |
|
|
|
|
| starlette_responses.guess_type = _hooked_guess_type |
|
|
|
|
| def run_train(toml_path: str): |
| print(f"Training started with config file / 训练开始，使用配置文件: {toml_path}") |
| args = [ |
| sys.executable, "-m", "accelerate.commands.launch", "--num_cpu_threads_per_process", "8", |
| "./sd-scripts/train_network.py", |
| "--config_file", toml_path, |
| ] |
| try: |
| result = subprocess.run(args, env=os.environ) |
| if result.returncode != 0: |
| print(f"Training failed / 训练失败") |
| else: |
| print(f"Training finished / 训练完成") |
| except Exception as e: |
| print(f"An error occurred when training / 创建训练进程时出现致命错误: {e}") |
| finally: |
| lock.release() |
|
|
|
|
| @app.middleware("http") |
| async def add_cache_control_header(request, call_next): |
| response = await call_next(request) |
| response.headers["Cache-Control"] = "max-age=0" |
| return response |
|
|
|
|
| @app.post("/api/run") |
| async def create_toml_file(request: Request, background_tasks: BackgroundTasks): |
| acquired = lock.acquire(blocking=False) |
|
|
| if not acquired: |
| print("Training is already running / 已有正在进行的训练") |
| return {"status": "fail", "detail": "Training is already running"} |
|
|
| timestamp = datetime.now().strftime("%Y%m%d-%H%M%S") |
| toml_file = os.path.join(os.getcwd(), f"toml", "autosave", f"{timestamp}.toml") |
| toml_data = await request.body() |
| j = json.loads(toml_data.decode("utf-8")) |
| with open(toml_file, "w") as f: |
| f.write(toml.dumps(j)) |
| background_tasks.add_task(run_train, toml_file) |
| return {"status": "success"} |
|
|
|
|
| @app.post("/api/interrogate") |
| async def run_interrogate(req: TaggerInterrogateRequest, background_tasks: BackgroundTasks): |
| background_tasks.add_task(on_interrogate, |
| image=None, |
| batch_input_glob=req.path, |
| batch_input_recursive=False, |
| batch_output_dir="", |
| batch_output_filename_format="[name].[output_extension]", |
| batch_output_action_on_conflict=req.batch_output_action_on_conflict, |
| batch_remove_duplicated_tag=True, |
| batch_output_save_json=False, |
| interrogator=interrogator, |
| threshold=req.threshold, |
| additional_tags=req.additional_tags, |
| exclude_tags=req.exclude_tags, |
| sort_by_alphabetical_order=False, |
| add_confident_as_weight=False, |
| replace_underscore=req.replace_underscore, |
| replace_underscore_excludes=req.replace_underscore_excludes, |
| escape_tag=req.escape_tag, |
| unload_model_after_running=True |
| ) |
| return {"status": "success"} |
|
|
|
|
| @app.get("/") |
| async def index(): |
| return FileResponse("./frontend/dist/index.html") |
|
|
|
|
| app.mount("/", StaticFiles(directory="frontend/dist"), name="static") |
|
|
