File size: 937 Bytes
5c0f8ba 61bb578 8f27613 5c0f8ba c05b93c 5c0f8ba 8f27613 5c0f8ba 164c46c 5c0f8ba 61bb578 8f27613 61bb578 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | from flask import Flask, request, jsonify
import joblib
import json
app = Flask(__name__)
# Load model
model = joblib.load("models/model.pkl")
# Load label mapping
with open("models/labels.json", "r") as f:
label_map = json.load(f)
@app.route("/")
def index():
return "Iris Classifier API is running!"
@app.route("/predict", methods=["POST"])
def predict():
try:
data = request.get_json()
features = [
float(data["sepal_length"]),
float(data["sepal_width"]),
float(data["petal_length"]),
float(data["petal_width"]),
]
prediction = model.predict([features])
pred_index = int(prediction[0])
pred_label = label_map.get(str(pred_index), "unknown")
return jsonify({
"prediction": pred_index,
"label": pred_label
})
except Exception as e:
return jsonify({"error": str(e)}), 400
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