Create app.py

app.py

@@ -0,0 +1,64 @@
+import pickle
+import gradio as gr
+
+# Load the pickled model
+with open('./RF with pipe.pickle', 'rb') as file:
+    model = pickle.load(file)
+
+# Define the function for making predictions
+def cerviccancer(Age, Num_sexual_partners, First_sexual_intercourse, Num_pregnancies, Smokes, Smokes_years, Smokes_packs_year, 
+                 Hormonal_Contraceptives, Hormonal_Contraceptives_years, IUD, IUD_years, STDs, STDs_condylomatosis, STDs_cervical_condylomatosis, 
+                 STDs_vaginal_condylomatosis, STDs_vulvoperineal_condylomatosis, STDs_syphilis, STDs_pelvic_inflammatory_disease, STDs_genital_herpes, 
+                 STDs_molluscum_contagiosum, STDs_AIDS, STDs_HIV, STDs_Hepatitis_B, STDs_HPV, STDs_Num_of_diagnosis, Dx_Cancer, Dx_CIN, Dx, Hinselmann, Schiller, Citology):
+    inputs = [[Age, Num_sexual_partners, First_sexual_intercourse, Num_pregnancies, Smokes, Smokes_years, Smokes_packs_year, 
+               Hormonal_Contraceptives, Hormonal_Contraceptives_years, IUD, IUD_years, STDs, STDs_condylomatosis, STDs_cervical_condylomatosis, 
+               STDs_vaginal_condylomatosis, STDs_vulvoperineal_condylomatosis, STDs_syphilis, STDs_pelvic_inflammatory_disease, STDs_genital_herpes, 
+               STDs_molluscum_contagiosum, STDs_AIDS, STDs_HIV, STDs_Hepatitis_B, STDs_HPV, STDs_Num_of_diagnosis, Dx_Cancer, Dx_CIN, Dx, Hinselmann, Schiller, Citology]]
+    prediction = model.predict(inputs)
+    prediction_value = prediction[0]
+    return f"Predicted probability of Biopsy: {prediction_value}"
+
+
+# Create the Gradio interface
+automatidata_ga = gr.Interface(fn=automatidata, 
+                               inputs = [
+                                            gr.Number(13.0, 84.0, label="Age"),
+                                            gr.Number(1.0, 28.0, label="Number of sexual partners"),
+                                            gr.Number(10.0, 32.0, label="First sexual intercourse"),
+                                            gr.Number(0.0, 11.0, label="Num of pregnancies"),
+                                            gr.Number(0.0, 1.0, label="Smokes"),
+                                            gr.Number(0.0, 37.0, label="Smokes (years)"),
+                                            gr.Number(0.0, 37.0, label="Smokes (packs/year)"),
+                                            gr.Number(0.0, 1.0, label="Hormonal Contraceptives"),
+                                            gr.Number(0.0, 30.0, label="Hormonal Contraceptives (years)"),
+                                            gr.Number(0.0, 1.0, label="IUD"),
+                                            gr.Number(0.0, 19.0, label="IUD (years)"),
+                                            gr.Number(0.0, 1.0, label="STDs"),
+                                            gr.Number(0.0, 1.0, label="STDs:condylomatosis"),
+                                            gr.Number(0.0, 0.0, label="STDs:cervical condylomatosis"),
+                                            gr.Number(0.0, 1.0, label="STDs:vaginal condylomatosis"),
+                                            gr.Number(0.0, 1.0, label="STDs:vulvo-perineal condylomatosis"),
+                                            gr.Number(0.0, 1.0, label="STDs:syphilis"),
+                                            gr.Number(0.0, 1.0, label="STDs:pelvic inflammatory disease"),
+                                            gr.Number(0.0, 1.0, label="STDs:genital herpes"),
+                                            gr.Number(0.0, 1.0, label="STDs:molluscum contagiosum"),
+                                            gr.Number(0.0, 0.0, label="STDs:AIDS"),
+                                            gr.Number(0.0, 1.0, label="STDs:HIV"),
+                                            gr.Number(0.0, 1.0, label="STDs:Hepatitis B"),
+                                            gr.Number(0.0, 1.0, label="STDs:HPV"),
+                                            gr.Number(0.0, 3.0, label="STDs: Number of diagnosis"),
+                                            gr.Number(0.0, 1.0, label="Dx:Cancer"),
+                                            gr.Number(0.0, 1.0, label="Dx:CIN"),
+                                            gr.Number(0.0, 1.0, label="Dx"),
+                                            gr.Number(0.0, 1.0, label="Hinselmann"),
+                                            gr.Number(0.0, 1.0, label="Schiller"),
+                                            gr.Number(0.0, 1.0, label="Citology"),
+                                            gr.Number(0.0, 1.0, label="Biopsy")
+                                        ]
+
+                               outputs="text", title="Cervical Cancer Risk Prediction", 
+                               description="Predicting probability of Biopsy Using Machine Learning.",
+                               theme='dark'
+                               )
+
+automatidata_ga.launch(auth = ('parthebhan','cerviccancer'),share=True)