import os
import numpy as np
import tensorflow as tf
from tensorflow import keras
import cv2

directory = "C:/Users/KimD/PycharmProjects/Traktor_V1/Vegetable Images/test"


class VegebatlesRecognizer:

    def recognize(self, image_path) -> str:
        model = keras.models.load_model("C:/Users/KimD/PycharmProjects/Traktor_V1/mode2.h5")
        class_names = ['Bean', 'Broccoli', 'Cabbage', 'Capsicum', 'Carrot', 'Cucumber', 'Potato', 'Pumpkin', 'Tomato']

        img = cv2.imread(image_path)
        # cv2.imshow("lala", img)
        # cv2.waitKey(0)
        img = (np.expand_dims(img, 0))

        predictions = model.predict(img)[0].tolist()

        print(class_names)
        print(predictions)
        print(max(predictions))
        print(predictions.index(max(predictions)))

        return class_names[predictions.index(max(predictions))]


# image_path = 'C:/Users/KimD/PycharmProjects/Traktor_V1/Vegetable Images/test/Carrot/1001.jpg'
# uio = VegebatlesRecognizer()
# print(uio.recognize(image_path))