Update app.py
Browse files
app.py
CHANGED
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@@ -19,25 +19,26 @@ poly = PolynomialFeatures(degree=5, include_bias=False)
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scaler = StandardScaler()
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#
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def preprocess_input(flange_width, beam_width,
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"""
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Preprocess the input data: apply polynomial features and then scale.
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"""
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# # Apply Polynomial Features
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# Standardize the polynomial features
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scaled_features = scaler_loaded.transform(X_test_poly)
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return scaled_features
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def predict_fatigue_crack_growth_rate(flange_width, beam_width,
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"""
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Function to predict the fatigue crack growth rate based on the preprocessed input features.
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"""
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# Preprocess the input data
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preprocessed_input = preprocess_input(flange_width, beam_width,
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# Predict using the loaded model
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prediction = model.predict(preprocessed_input)
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@@ -47,12 +48,14 @@ def predict_fatigue_crack_growth_rate(flange_width, beam_width, geometric_factor
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# Create a Gradio interface
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iface = gr.Interface(fn=predict_fatigue_crack_growth_rate,
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inputs=[gr.Number(label="
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gr.Number(label="Beam Width"),
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gr.Number(label="
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outputs=gr.Textbox(label="Prediction"),
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title="Fatigue Crack Growth Rate Predictor",
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description="Enter the values for Column Width, Beam Width, and
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if __name__ == "__main__":
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iface.launch()
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scaler = StandardScaler()
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#
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def preprocess_input(eometric_factor, flange_width, beam_width, beamh, columntw):
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"""
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Preprocess the input data: apply polynomial features and then scale.
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"""
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# # Apply Polynomial Features
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# ['GEOMETRIC_FACTOR', 'COLUMN_WIDTH', 'BEAM_WIDTH','BEAM - h', 'COLUMN - tw']
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X_test_poly = poly_loaded.transform([[eometric_factor, flange_width, beam_width, beamh, columntw]])
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# Standardize the polynomial features
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scaled_features = scaler_loaded.transform(X_test_poly)
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return scaled_features
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def predict_fatigue_crack_growth_rate(geometric_factor, flange_width, beam_width, beamh, columntw):
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"""
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Function to predict the fatigue crack growth rate based on the preprocessed input features.
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"""
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# Preprocess the input data
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preprocessed_input = preprocess_input(eometric_factor, flange_width, beam_width, beamh, columntw)
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# Predict using the loaded model
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prediction = model.predict(preprocessed_input)
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# Create a Gradio interface
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iface = gr.Interface(fn=predict_fatigue_crack_growth_rate,
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inputs=[gr.Number(label="Geometric Factor")],
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gr.Number(label="Column Width"),
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gr.Number(label="Beam Width"),
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gr.Number(label="Beam - h"),
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gr.Number(label="Column - tw"),
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outputs=gr.Textbox(label="Prediction"),
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title="Fatigue Crack Growth Rate Predictor",
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description="Enter the values for Geometric Factor, Column Width, Beam Width, Beam - h, and COLUMN - tw to predict the Fatigue Crack Growth Rate.")
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if __name__ == "__main__":
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iface.launch()
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