Initial

.gitignore

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+MISC/

README.md

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 ---
-title: TSPIzeimer2
-emoji: 🏃
-colorFrom: red
-colorTo: red
+title: STPIzeimer
+emoji: 👀
+colorFrom: purple
+colorTo: green
 sdk: gradio
-sdk_version: 3.0.24
 app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Configuration
+
+`title`: _string_  
+Display title for the Space
+
+`emoji`: _string_  
+Space emoji (emoji-only character allowed)
+
+`colorFrom`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`colorTo`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`sdk`: _string_  
+Can be either `gradio` or `streamlit`
+
+`sdk_version` : _string_  
+Only applicable for `streamlit` SDK.  
+See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
+
+`app_file`: _string_  
+Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
+Path is relative to the root of the repository.
+
+`pinned`: _boolean_  
+Whether the Space stays on top of your list.

STPI_3WAY_RandomForest.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e44d33f4a94990903d888315af904467280eb7aa74982a0fcc158604ea579700
+size 308096

app.py

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+# %%
+import gradio as gr
+import 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','Suspect','Keratoconic']
+    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_3way = loaded_rf_3way.predict([X])
+    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='Uses the Thickness Speed Progression Index (TSPI) to calculate the most probable patient diagnosis 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
+    )
+# %%

requirements.txt

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+gradio==2.4.6
+joblib==1.0.0
+scikit-learn==0.24.0

stpi_data.txt

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+11.0;22.0;33.0;44.0;55.0;66.0;77.0