#!/usr/bin/env python3
import cv2
import numpy as np
import os
from joblib import load


class SVMModel:
    def __init__(self):
        path = os.getenv("SVM_MODEL_PATH", "/home/user/app/model_classification/svm_model.joblib")
        self.model = load(path)

    def classify_image(
        self,
        image_bytes: bytes,
        image_size=(128, 128)
    ) -> int:
        img = cv2.imdecode(np.frombuffer(image_bytes, np.uint8), cv2.IMREAD_COLOR)
        if img is None:
            # If image fails to load, default to "irrelevant" or handle differently
            return 0

        img = cv2.resize(img, image_size)
        x = img.flatten().reshape(1, -1)
        pred = self.model.predict(x)[0]
        return pred

if __name__ == "__main__":
    model = load_svm_model("/home/user/app/model_classification/svm_model_2.joblib")
    result = classify_image("test.jpg", model)
    print("Classification result:", result)