Spaces:
Sleeping
Sleeping
JadAssaf
commited on
Commit
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dc45fa4
1
Parent(s):
c4381f3
initial
Browse files- .DS_Store +0 -0
- .gitignore +1 -0
- STPI_2WAY_RandomForest.joblib +3 -0
- STPI_3WAY_RandomForest.joblib +3 -0
- app.py +62 -0
- requirements.txt +3 -0
- stpi_data.txt +1 -0
.DS_Store
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Binary file (8.2 kB). View file
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.gitignore
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MISC/
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STPI_2WAY_RandomForest.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:84ae3aec58b4bf3cfe625ac2138d6ac245f741787070ea7ae2538f404029fc5a
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size 86585
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STPI_3WAY_RandomForest.joblib
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version https://git-lfs.github.com/spec/v1
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oid sha256:2404d314d346836902a186594bbeb9371f822b07aabe863d07c3777ddca05875
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size 95873
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app.py
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# %%
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import gradio as gr
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import joblib
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loaded_rf_2way = joblib.load("STPI_2WAY_RandomForest.joblib")
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loaded_rf_3way = joblib.load("STPI_3WAY_RandomForest.joblib")
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def STPI(t_0_5_MaxValue,t_1_0_MaxValue,t_2_0_MaxValue,
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# Acc_0_5__1_0_MaxValue,
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Abs_Diff_t_0_5_MaxValue,Abs_Diff_t_1_0_MaxValue,Abs_Diff_t_2_0_MaxValue,Optional_Custom_Message='No_Message'):
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print('------------------')
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print(Optional_Custom_Message)
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X = [t_0_5_MaxValue,t_1_0_MaxValue,t_2_0_MaxValue,
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# Acc_0_5__1_0_MaxValue,
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Abs_Diff_t_0_5_MaxValue,Abs_Diff_t_1_0_MaxValue,Abs_Diff_t_2_0_MaxValue]
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print(X)
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outcome_decoded = ['Normal','Keratoconic','Suspect']
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file_object = open('stpi_data.txt', 'a')
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file_object.write(str(t_0_5_MaxValue))
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file_object.write(';')
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file_object.write(str(t_1_0_MaxValue))
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file_object.write(';')
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file_object.write(str(t_2_0_MaxValue))
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file_object.write(';')
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# file_object.write(str(Acc_0_5__1_0_MaxValue))
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# file_object.write(';')
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file_object.write(str(Abs_Diff_t_0_5_MaxValue))
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file_object.write(';')
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file_object.write(str(Abs_Diff_t_1_0_MaxValue))
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file_object.write(';')
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file_object.write(str(Abs_Diff_t_2_0_MaxValue))
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file_object.write(';')
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file_object.write(Optional_Custom_Message)
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file_object.write('\n')
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file_object.close()
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result_2way = loaded_rf_2way.predict([X])
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print('The patient is ', outcome_decoded[int(result_2way)], ' through the 2way method')
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result_3way = loaded_rf_3way.predict([X])
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if result_2way == 0:
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print('The patient is ', outcome_decoded[int(result_3way)], 'through the 3way method')
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# result = 'The 3-way classification resulted in a ', outcome_decoded[int(result_3way)] + ' patient.'
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# further_analysis = 'Futher analysis using the 2-way classification resulted in a ' + outcome_decoded[int(result_2way)] + ' label.'
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return 'The 3-way classification resulted in a ' + outcome_decoded[int(result_3way)] + ' patient. Futher analysis using the 2-way classification resulted in a ' + outcome_decoded[int(result_2way)] + ' label.'
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# result = 'The 2-way classification resulted in a ', outcome_decoded[int(result_2way)] + ' patient.'
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# further_analysis = 'Futher analysis using the 3-way classification resulted in a ' + outcome_decoded[int(result_3way)] + ' label.'
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return 'The 2-way classification resulted in a ' + outcome_decoded[int(result_2way)] + ' patient. Futher analysis using the 3-way classification resulted in a ' + outcome_decoded[int(result_3way)] + ' label.'
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iface = gr.Interface(
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fn=STPI,
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title='STPI Calculator',
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description='Calculates the STPI through summarized tomographic parameters. Beta version by Prof. Shady Awwad, Jad Assaf MD and Jawad Kaisania.',
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inputs=["number", "number","number",
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# "number",
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"number", "number","number","text"],
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outputs="text")
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iface.launch(share=True)
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# %%
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requirements.txt
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gradio==2.4.6
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joblib==1.0.0
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scikit-learn==0.24.0
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stpi_data.txt
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11.0;22.0;33.0;44.0;55.0;66.0;77.0
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