Flask Iris Classifier API
from flask import Flask | |
from flask import request | |
import joblib | |
import pandas as pd | |
import json | |
with open("iris_classifier.joblib", "rb") as f: | |
iris_classifier = joblib.load(f) | |
with open("iris_classifier_features.joblib", "rb") as f: | |
iris_classifier_features = joblib.load(f) | |
app = Flask(__name__) | |
@app.route('/predict-species', methods=['POST']) | |
def predict_species(): | |
flower = {} | |
for feature in iris_classifier_features: | |
flower[feature] = [request.form[feature]] | |
flower = pd.DataFrame(flower) | |
species = iris_classifier.predict(flower[iris_classifier_features]) | |
return species[0] |
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