AliMustapha commited on
Commit
86ee792
·
1 Parent(s): 9d378bb

some changing

Browse files
Files changed (3) hide show
  1. Dictionary_guesser/__init__.py +0 -0
  2. __init__.py +0 -0
  3. app.py +3 -2
Dictionary_guesser/__init__.py ADDED
File without changes
__init__.py ADDED
File without changes
app.py CHANGED
@@ -10,6 +10,8 @@ import utils.plot as plot
10
  class GenderPredictorApp:
11
  def __init__(self, modelpath):
12
  self.gender_predictor = GenderPredictor(modelpath)
 
 
13
  self.setup_ui()
14
 
15
  def setup_ui(self):
@@ -44,13 +46,12 @@ class GenderPredictorApp:
44
  return prediction
45
  def predict_github_url(self, url):
46
  commit_info = CommitInfo(url)
47
- Region_predictor=RegionPredictor("saved_model/Regions")
48
  df,first_commit_dates = commit_info.get_first_commit_dates()
49
  first_commit_dates[['Predicted_Gender', 'Confidence']] = first_commit_dates['Author'].apply(lambda name: pd.Series(self.gender_predictor.predict_gender(name)))
50
  first_commit_dates['Predicted_Gender'] = first_commit_dates['Predicted_Gender'].replace({0: "Male", 1: "Female", 2: "Unknown"})
51
  Gender_Percentage=plot.get_gender_percentage(first_commit_dates)
52
  Results=first_commit_dates[first_commit_dates["Predicted_Gender"]!="Unknown"]
53
- Results=Region_predictor.get_region(Results)
54
 
55
  merged_df = df.merge(Results[["Author","sub-region-prediction","Predicted_Gender","Confidence"]], on=["Author"])
56
  # Group by Year and Predicted_Gender, then count the occurrences
 
10
  class GenderPredictorApp:
11
  def __init__(self, modelpath):
12
  self.gender_predictor = GenderPredictor(modelpath)
13
+ self.Region_predictor=RegionPredictor("saved_model/Regions")
14
+
15
  self.setup_ui()
16
 
17
  def setup_ui(self):
 
46
  return prediction
47
  def predict_github_url(self, url):
48
  commit_info = CommitInfo(url)
 
49
  df,first_commit_dates = commit_info.get_first_commit_dates()
50
  first_commit_dates[['Predicted_Gender', 'Confidence']] = first_commit_dates['Author'].apply(lambda name: pd.Series(self.gender_predictor.predict_gender(name)))
51
  first_commit_dates['Predicted_Gender'] = first_commit_dates['Predicted_Gender'].replace({0: "Male", 1: "Female", 2: "Unknown"})
52
  Gender_Percentage=plot.get_gender_percentage(first_commit_dates)
53
  Results=first_commit_dates[first_commit_dates["Predicted_Gender"]!="Unknown"]
54
+ Results=self.Region_predictor.get_region(Results)
55
 
56
  merged_df = df.merge(Results[["Author","sub-region-prediction","Predicted_Gender","Confidence"]], on=["Author"])
57
  # Group by Year and Predicted_Gender, then count the occurrences