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Update app.py
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app.py
CHANGED
@@ -24,6 +24,11 @@ importlib.reload(streamlit_presentation.modele)
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from streamlit_presentation.modele import presentation_modele
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from sklearn.metrics import f1_score
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plt.rcParams['font.size'] = 12
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plt.rcParams['axes.labelsize'] = 10
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plt.rcParams['axes.titlesize'] = 12
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@@ -38,6 +43,9 @@ extract_data = pd.read_csv( 'data_tr_extract.csv')
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sum_data = pd.read_csv( 'data_sum_extract.csv')
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test_data = pd.read_pickle( 'data_test.pkl')
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from keras.models import load_model
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import tensorflow as tf
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from tensorflow.keras import backend as K
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@@ -166,7 +174,7 @@ elif tabs == "Modèle":
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presentation_modele(st, test_data, model,class_labels,y_test,encoder)
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elif tabs == "Pistes exploratoires":
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st.write("
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st
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from streamlit_presentation.modele import presentation_modele
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from sklearn.metrics import f1_score
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import streamlit_presentation.plusloin
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importlib.reload(streamlit_presentation.plusloin)
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from streamlit_presentation.plusloin import plusloin
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plt.rcParams['font.size'] = 12
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plt.rcParams['axes.labelsize'] = 10
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plt.rcParams['axes.titlesize'] = 12
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sum_data = pd.read_csv( 'data_sum_extract.csv')
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test_data = pd.read_pickle( 'data_test.pkl')
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from tensorflow.keras.models import load_model
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autoencoder = load_model('autoencoder_model.h5')
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from keras.models import load_model
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import tensorflow as tf
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from tensorflow.keras import backend as K
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presentation_modele(st, test_data, model,class_labels,y_test,encoder)
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elif tabs == "Pistes exploratoires":
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st.write("### Pistes exploratoires")
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plusloin(st,autoencoder)
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