adsf

app.py

@@ -5,10 +5,6 @@ import requests
 import pandas as pd
 import matplotlib.pyplot as plt
 import numpy as np
-from sklearn import preprocessing
-from sklearn.model_selection import train_test_split
-from sklearn.ensemble import RandomForestRegressor
-
 
 import hopsworks
 import joblib
@@ -88,12 +84,8 @@ def titanic(Pclass, Sex, Age, SibSp, Parch, Fare, Embarked):
 
     survived = res[0]
 
-    # Temp:
-    age = 20
-    gender = "female"
-
     # Todo: survivor, "https://fakeface.rest/face/json?maximum_age=50&gender=female&minimum_age=49"
-    generate_survivor_url = f'https://fakeface.rest/face/json?maximum_age={Age}&gender={Sex}&minimum_age={age}'
+    generate_survivor_url = f'https://fakeface.rest/face/json?maximum_age={Age}&gender={Sex}&minimum_age={Age}'
     randomized_face_url = requests.get(
         generate_survivor_url).json()["image_url"]
 

requirements.txt

@@ -1,6 +1,5 @@
 hopsworks
 joblib
-scikit-learn
 gradio
 numpy
 pandas