27 lines
770 B
Python
27 lines
770 B
Python
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import numpy as np
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#from neural_network import *
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from numpy import loadtxt
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import pandas as pd
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from sklearn.model_selection import train_test_split
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import tensorflow as tf
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from tensorflow.keras.layers import Dense, Dropout
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products = ['glass', 'mixed', 'metal', 'paper']
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n_products = len(products)
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data = pd.read_csv("X_test.csv")
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dff = data.loc[:, data.columns != 'Unnamed: 0']
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def b():
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a = dff.sample()
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pred(a)
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model = tf.keras.models.load_model('C:/Users/Natalia/Desktop/lsm04/smieciara/saved_model')
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def pred(a):
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print(a)
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prediction_proba = model.predict(np.array(a))
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prediction = np.argmax(prediction_proba)
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text_representation = products[prediction]
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print(text_representation)
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print(prediction)
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return prediction
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