48 lines
1.1 KiB
Python
48 lines
1.1 KiB
Python
from tkinter import PhotoImage
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import cv2
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import tensorflow as tf
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import numpy as np
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from keras_preprocessing.image import ImageDataGenerator
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from bin.Classess.Field import Field
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field = Field()
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CATEGORIES = ['houses', 'other']
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def prepare(filepath):
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IMG_SIZE = 400
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img_array = cv2.imread(filepath)
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new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))
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new_array = np.array(new_array) / 255
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return new_array.reshape(1, IMG_SIZE, IMG_SIZE, 3)
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model = tf.keras.models.load_model("../../files/Neural_networks/model/training_50_epochs")
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model.summary()
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test = prepare("E:/Projects/Pycharm Projects/sapper/files/large_images_houses/IMG_2573.png")
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# test = prepare("E:/Projects/Pycharm Projects/sapper/files/large_images/IMG_3208.png")
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pred = test
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prediction = model.predict([pred])
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print(prediction) # will be a list in a list.
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house = prediction[0][0]
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other = prediction[0][1]
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if house > other:
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prediction = 0
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else:
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prediction = 1
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print(f'house: {house}\nother: {other}')
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print(f'prediction: {prediction}')
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print(CATEGORIES[int(prediction[0][0])])
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