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import imghdr
from os import name
from fastapi import FastAPI, Response, UploadFile
from pydantic import BaseModel
import time
import pickle
import numpy as np
import uvicorn
from models import classe
app = FastAPI()
pickle_in = open("classifier.pkl","rb")
classifier = pickle.load(pickle_in)
@app.get("/")
def index():
return {"hello": "FastAPI"}
@app.get('/{name}')
def get_name(name: str):
return {'message': f'hello, {name}'}
@app.post('/predict')
def predict_species(data: classe):
Sepal_Length = data.Sepal_Length
Sepal_Width = data.Sepal_Width
Petal_Length = data.Petal_Length
Petal_Width = data.Petal_Width
prediction = classifier.predict([[Sepal_Length, Sepal_Width, Petal_Length, Petal_Width]])
if prediction[0] == 0:
species = "setosa"
elif prediction[0] == 1:
species = "virginica"
elif prediction[0] == 2:
species = "versicolor"
else:
species = "unknown"
return {'prediction': species}
if __name__ == "__main__":
uvicorn.run(app, host="127.0.0.1", port=8000)
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