# %% import gradio as gr import joblib loaded_rf_2way = joblib.load("STPI_2WAY_RandomForest.joblib") loaded_rf_3way = joblib.load("STPI_3WAY_RandomForest.joblib") def STPI(t_0_5_MaxValue,t_1_0_MaxValue,t_2_0_MaxValue, # Acc_0_5__1_0_MaxValue, Abs_Diff_t_0_5_MaxValue,Abs_Diff_t_1_0_MaxValue,Abs_Diff_t_2_0_MaxValue): print('------------------') X = [t_0_5_MaxValue,t_1_0_MaxValue,t_2_0_MaxValue, # Acc_0_5__1_0_MaxValue, Abs_Diff_t_0_5_MaxValue,Abs_Diff_t_1_0_MaxValue,Abs_Diff_t_2_0_MaxValue] print(X) outcome_decoded = ['Normal','Keratoconic','Suspect'] file_object = open('stpi_data.txt', 'a') file_object.write(str(t_0_5_MaxValue)) file_object.write(';') file_object.write(str(t_1_0_MaxValue)) file_object.write(';') file_object.write(str(t_2_0_MaxValue)) file_object.write(';') # file_object.write(str(Acc_0_5__1_0_MaxValue)) # file_object.write(';') file_object.write(str(Abs_Diff_t_0_5_MaxValue)) file_object.write(';') file_object.write(str(Abs_Diff_t_1_0_MaxValue)) file_object.write(';') file_object.write(str(Abs_Diff_t_2_0_MaxValue)) file_object.write(';') file_object.write('\n') file_object.close() result_2way = loaded_rf_2way.predict([X]) print('The patient is ', outcome_decoded[int(result_2way)], ' through the 2way method') result_3way = loaded_rf_3way.predict([X]) if result_2way == 0: print('The patient is ', outcome_decoded[int(result_3way)], 'through the 3way method') # result = 'The 3-way classification resulted in a ', outcome_decoded[int(result_3way)] + ' patient.' # further_analysis = 'Futher analysis using the 2-way classification resulted in a ' + outcome_decoded[int(result_2way)] + ' label.' return 'The patient is ' + outcome_decoded[int(result_3way)] + '.' # result = 'The 2-way classification resulted in a ', outcome_decoded[int(result_2way)] + ' patient.' # further_analysis = 'Futher analysis using the 3-way classification resulted in a ' + outcome_decoded[int(result_3way)] + ' label.' return 'The patient is ' + outcome_decoded[int(result_2way)] + '.' iface = gr.Interface( fn=STPI, title='TSPI Calculator', description='Calculates the Thickness Speed Progression Index (TSPI) through summarized tomographic parameters. Beta version made for Zeimer by Prof. Shady Awwad and Jad Assaf MD.', inputs=["number", "number","number", # "number", "number", "number","number"], outputs="text") iface.launch( # share=True ) # %%