code cleaning

app.py

@@ -7,16 +7,16 @@ from GitScraping import CommitInfo
 from get_region import RegionPredictor
 import pandas as pd
 import utils.plot as plot 
+
+
 class GenderPredictorApp:
     def __init__(self, modelpath):
         self.gender_predictor = GenderPredictor(modelpath)
-        self.Region_predictor=RegionPredictor("saved_model/Regions")
+        self.Region_predictor=RegionPredictor(models_directory="saved_model/Regions")
         
         self.setup_ui()
 
     def setup_ui(self):
-        # with gr.Blocks() as demo:
-        # gr.Label(value="Exploring Global Gender Disparities in Public Code Contributions")
         name = gr.inputs.Textbox(label="Name")
         output = gr.outputs.Textbox(label="Predicted Gender")
         interface1_fn = gr.Interface(fn=self.predict_name, inputs=name, outputs=output, title="GitGender: Exploring Global Gender Disparities in Public Code Contributions",cache_examples=True )
@@ -25,7 +25,6 @@ class GenderPredictorApp:
         histo_chart = gr.Plot(label="Known commits by gender")
         region_commits = gr.Plot(label="Known commits by gender")
         data_output =gr.Dataframe(headers=None,label="Contributers Details")
-        # name_buttom = gr.Button("Predict")
         interface2_fn = gr.Interface(self.predict_github_url, inputs=name, outputs=[pie_chart_output, histo_chart,region_commits,data_output], title="GitGender: Exploring Global Gender Disparities in Public Code Contributions" )
         demo = gr.TabbedInterface([interface1_fn, interface2_fn], ["Test Model", "Exploring Diversity in GitHub Repositories"])
         self.demo = demo
@@ -34,7 +33,6 @@ class GenderPredictorApp:
 
     def predict_name(self, name):
         prediction, proba = self.gender_predictor.predict_gender(name)
-
         if prediction == 0:
             prediction = "Male with probability: " + str(proba) + "%"
         elif prediction == 1:
@@ -59,7 +57,7 @@ class GenderPredictorApp:
         commit_per_gender_counts = merged_df.groupby(['Year', 'Predicted_Gender']).size().reset_index(name='Count')
         commits_per_gender=plot.get_commits_per_gender(commit_per_gender_counts)
         commits_per_region=plot.get_commits_per_region(merged_df,url)
-        # Convert the chart to HTML and return it
+        
         return Gender_Percentage,commits_per_gender,commits_per_region,Results[["Author","sub-region-prediction","Predicted_Gender","First_Commit_Date"]]
     def launch(self):
         self.demo.launch()