main.py

from fastapi import FastAPI, File, UploadFile
from pydantic import BaseModel
from torchvision.transforms import ToTensor
from PIL import Image
import torch
import os
from fastapi.middleware.cors import CORSMiddleware
from loguru import logger
from inference import print_model


import time

# from colabcode import ColabCode
# cc = ColabCode(port=8000, code=False)

app = FastAPI()

origins = [
    "*"
]

app.add_middleware(
    CORSMiddleware,
    allow_origins=origins,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)


@app.post("/photo")
async def create_upload_file(file: UploadFile = File(...)):

  ################################파일 업로드 부분#####################################
  # UPLOAD_DIR = "./photo"  # 이미지를 저장할 서버 경로
    
  # content = await file.read()
  # filename = "test.jpg"  # uuid로 유니크한 파일명으로 변경
  # with open(os.path.join(UPLOAD_DIR, filename), "wb") as fp:
  #     fp.write(content)
  # print("@@@@@@@@@@이미지 업로드 완료!! @@@@@@@@@@@")
  ####################################################################################
  # image = ToTensor()(Image.open(file.file))
  # output = model(image)
  # logger.info("Classify Result = {}", output)

  start = time.time()
  result = print_model("resnet18",file.file,"./weights/resnet18_qat.pt","qat")
  print(result)
  print(time.time() - start)
  return result






class Model(BaseModel):
    name: str
    phoneNumber: int

@app.get("/")
def 이름():
  return '보낼 값'

@app.post("/send")
def data받기(data : Model):
  print(data)
  return '전송완료'

# cc.run_app(app=app)