34 lines
1.0 KiB
Python
34 lines
1.0 KiB
Python
import os
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import numpy as np
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import tensorflow as tf
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from tensorflow import keras
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import cv2
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directory = "C:/Users/KimD/PycharmProjects/Traktor_V1/Vegetable Images/test"
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class VegebatlesRecognizer:
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model = keras.models.load_model("C:/Users/KimD/PycharmProjects/sztin_gr.234798/recognition_v1/mode1.h5")
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def recognize(self, image_path) -> str:
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class_names = ['Broccoli', 'Capsicum', 'Carrot', 'Potato']
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img = cv2.imread(image_path)
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# cv2.imshow("lala", img)
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# cv2.waitKey(0)
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img = (np.expand_dims(img, 0))
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predictions = self.model.predict(img)[0].tolist()
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# print(class_names)
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# print(predictions)
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# print(max(predictions))
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# print(predictions.index(max(predictions)))
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return class_names[predictions.index(max(predictions))]
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# image_path = 'C:/Users/KimD/PycharmProjects/Traktor_V1/Vegetable Images/test/Carrot/1001.jpg'
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# uio = VegebatlesRecognizer()
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# print(uio.recognize(image_path))
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