identification-nn's Introduction

API description

1.エンドポイント


class Request(BaseModel):
    similarity : float
    date_difference : float

https://fast-api-production.up.railway.app/path/

similarity : コサイン類似度・float
date_difference : 日付のズレをmsにしたもの

@app.post("/predict/", response_model=Response)
async def demo_get_path_id(req_body: Request):
    try:
        ch_sec = req_body.date_id / 1000 / 1000
        date_std = (ch_sec - mean)/std
        new_data = np.array([[req_body.cos_id, date_std]])
        if ch_sec >= 400:
            return Response(data=[0, 1])
        else:
            return Response(data=[model.predict(new_data)[0],model.predict(new_data)[1]])

    except Exception as e:
        return Response(data=[-1, 1], error=str(e))

2.戻り値

class Response(BaseModel):
    data: [float, float]
    error: Optional[str] = None

{"res":[rate_true,rate_false]}

rate_true : その人の落とし物である確率
rate_false : その人の落とし物でない確率

FastAPI Example

This example starts up a FastAPI server.

✨ Features

FastAPI
Python 3

💁‍♀️ How to use

Deploy using the button 👆
Clone locally and install packages with Pip using pip install -r requirements.txt or Poetry using poetry install
Connect to your project using railway link
Run locally using uvicorn main:app --reload

📝 Notes

To learn about how to use FastAPI with most of its features, you can visit the FastAPI Documentation.
FastAPI provides automatic documentation to call and test your API directly from the browser. You can access it at /docs with Swagger or at /redoc with Redoc.

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