main.py

import sys

import uvicorn
import yaml
from fastapi import (
    FastAPI,
    File,
    HTTPException,
    Request,
    UploadFile,
)
from fastapi.datastructures import UploadFile
from fastapi.responses import HTMLResponse
from fastapi.templating import Jinja2Templates

from src.convnet.nodes.etl import read_convert_image
from src.convnet.nodes.prep import to_gray
from src.convnet.pipes import inference

# web page templating
# get jinja templates' path
templates = Jinja2Templates(directory="templates")

# instantiate web server
app = FastAPI()

# get parameters
params_path = "conf/parameters.yml"
with open(params_path) as file:
    PARAMS = yaml.safe_load(file)


# @app.get("/")
# def home():
#     return {"Home"}


@app.get("/")
# async def predict(img: UploadFile = File(...)):
async def predict():

    # # handle exceptions
    # if img is None or img.file is None:
    #     raise HTTPException(
    #         status_code=400,
    #         detail="Please provide an image",
    #     )
    # ext = img.filename.split(".")[-1] in (
    #     "jpg",
    #     "jpeg",
    #     "png",
    # )
    # # check extension
    # if not ext:
    #     raise HTTPException(
    #         status_code=400,
    #         detail="Please load a .jpg or .png",
    #     )
    # # preprocesisng
    # # make (height, width, 3) RGB
    # img_data = read_convert_image(
    #     img.file.read(), height=28, width=28
    # )
    # # make (height, width, 1) gray
    # img_data = to_gray(img_data)
    # predicted = inference.run(img_data)
    from ipdb import set_trace; set_trace()
    predicted = inference.run()
    return {"prediction:", predicted}


@app.get("/items/{id}", response_class=HTMLResponse)
async def read_item(request: Request, id: str):
    return templates.TemplateResponse(
        "item.html", {"request": request, "id": id}
    )


if __name__ == "__main__":
    """
    entry point
    usage:
        # training
        python main.py train
    """

    # get run argument
    args = sys.argv
    is_arg = len(args) == 2

    # # choose task
    # if is_arg and args[1] == "train":
    #     print("training")
    #     train.run(params=PARAMS)
    if is_arg and args[1] == "web_serve":
        print("serving web")
        uvicorn.run(app,host="localhost", port=5000)
        # uvicorn.run(app,host="0.0.0.0", port=5000)