MohamedRabie26
commited on
Commit
•
1e6306f
1
Parent(s):
9f0ca63
Update app.py
Browse files
app.py
CHANGED
@@ -3,8 +3,8 @@ import joblib
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from PIL import Image
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# Load already saved pipelines
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best_model_cs = joblib.load("
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best_model_co2 = joblib.load("
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# Prediction function for compressive strength model
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def make_prediction(Fly_ash, GGBS_GGBFS, Fine_aggregate, Na2SiO3_solution, NaOH_solution, NaOH_concentration, Superplasticiser, Curing_temperature, Curing_Period, Testing_Age):
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@@ -12,23 +12,24 @@ def make_prediction(Fly_ash, GGBS_GGBFS, Fine_aggregate, Na2SiO3_solution, NaOH_
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predt_co2 = best_model_co2.predict([[Fly_ash, GGBS_GGBFS, Fine_aggregate, Na2SiO3_solution, NaOH_solution, NaOH_concentration, Superplasticiser, Curing_temperature, Curing_Period, Testing_Age]])
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value_cs = round(predt_cs[0], 3)
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value_co2 = round(predt_co2[0], 3)
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image_component = gr.Image("MOO
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return value_cs, value_co2, image_component,
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# Inputs for the models
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inputs = [
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gr.Slider(
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gr.Slider(0, 711.0, label='GGBS or GGBFS (Kg/m³)', info="Amount of Ground Granulated Blast Furnace Slag(Kg/m³)"),
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gr.Slider(
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gr.Slider(
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gr.Slider(
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gr.Slider(0, 16.0, label='NaOH concentration (M)', info="Sodium Hydroxide concentration (M)"),
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gr.Slider(0, 35.555, label='Superplasticiser (kg/m³)', info="Amount of Superplasticiser (kg/m³)"),
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gr.Slider(
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gr.Slider(1,
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gr.Slider(1, 180, label='Testing Age (days)'),
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]
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# Outputs for both models
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outputs = [
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gr.Textbox(label="Compressive strength (MPa)"),
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from PIL import Image
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# Load already saved pipelines
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best_model_cs = joblib.load("modelCS_V3.pkl")
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best_model_co2 = joblib.load("modelCO2_V3.pkl")
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# Prediction function for compressive strength model
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def make_prediction(Fly_ash, GGBS_GGBFS, Fine_aggregate, Na2SiO3_solution, NaOH_solution, NaOH_concentration, Superplasticiser, Curing_temperature, Curing_Period, Testing_Age):
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predt_co2 = best_model_co2.predict([[Fly_ash, GGBS_GGBFS, Fine_aggregate, Na2SiO3_solution, NaOH_solution, NaOH_concentration, Superplasticiser, Curing_temperature, Curing_Period, Testing_Age]])
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value_cs = round(predt_cs[0], 3)
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value_co2 = round(predt_co2[0], 3)
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image_component = gr.Image("MOO results_V3.png", label="multi-objective optimization", type="pil")
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return value_cs, value_co2, image_component,
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# Inputs for the models
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inputs = [
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gr.Slider(20, 961.0, label='Fly ash (Kg/m³)', info="Amount of Fly ash (Kg/m³)"),
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gr.Slider(0, 711.0, label='GGBS or GGBFS (Kg/m³)', info="Amount of Ground Granulated Blast Furnace Slag(Kg/m³)"),
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gr.Slider(100, 1956.0, label='Fine aggregate (Kg/m³)', info="Amount of Fine aggregate (Kg/m³)"),
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gr.Slider(10, 531.0, label='Na₂SiO₃ solution (Kg/m³)', info="Amount of Sodium Silicate solution (Kg/m³)"),
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gr.Slider(10, 284.44, label='NaOH solution (Kg/m³)', info="Amount of Sodium Hydroxide solution (Kg/m³)"),
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gr.Slider(0, 16.0, label='NaOH concentration (M)', info="Sodium Hydroxide concentration (M)"),
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gr.Slider(0, 35.555, label='Superplasticiser (kg/m³)', info="Amount of Superplasticiser (kg/m³)"),
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gr.Slider(20, 120, label='Curing temperature (°C)'),
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gr.Slider(1, 90, label='Curing Period (days)', info="For curing temperature more than 30 °C the curing period should be maximum of 3 days"),
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gr.Slider(1, 180, label='Testing Age (days)', info="For curing temperature less than 30 °C the testing age should be equal to the curing period"),
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]
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+
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# Outputs for both models
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outputs = [
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gr.Textbox(label="Compressive strength (MPa)"),
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