import json

def load_model(config_path="model_config.json"):
    with open(config_path) as f:
        return json.load(f)

def predict_length(gt_value, config):
    coef = config["coefficients"]
    if config["model_type"] == "log_log_power_regression":
        return coef["a"] * (gt_value ** coef["b"])
    else:
        return coef["intercept"] + coef["slope"] * gt_value

if __name__ == "__main__":
    cfg = load_model()
    gt = float(input("Masukkan nilai GT: "))
    print("Prediksi Length:", predict_length(gt, cfg))