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added images
Browse files
app.py
CHANGED
@@ -3,6 +3,7 @@ import numpy as np
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.neighbors import KNeighborsClassifier
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def train_iris_model():
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df = pd.read_csv("Iris.csv")
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df['Species'] = df['Species'].map({'Iris-setosa': 0, 'Iris-virginica': 1, 'Iris-versicolor': 2})
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@@ -50,5 +51,13 @@ def main():
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st.subheader("Prediction:")
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st.success(f"Predicted Species: {predicted_species}")
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if __name__ == "__main__":
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main()
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import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.neighbors import KNeighborsClassifier
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def train_iris_model():
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df = pd.read_csv("Iris.csv")
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df['Species'] = df['Species'].map({'Iris-setosa': 0, 'Iris-virginica': 1, 'Iris-versicolor': 2})
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st.subheader("Prediction:")
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st.success(f"Predicted Species: {predicted_species}")
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# Display relevant images based on prediction
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if predicted_species == 'Iris-setosa':
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st.image('setosa_image.jpg', caption='Iris-setosa', use_column_width=True)
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elif predicted_species == 'Iris-virginica':
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st.image('virginica_image.jpg', caption='Iris-virginica', use_column_width=True)
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elif predicted_species == 'Iris-versicolor':
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st.image('versicolor_image.jpg', caption='Iris-versicolor', use_column_width=True)
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if __name__ == "__main__":
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main()
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