| import numpy as np | |
| import pandas as pd | |
| import streamlit as st | |
| import joblib | |
| from apify_client import ApifyClient | |
| model = joblib.load("classifier.pkl") | |
| client = ApifyClient("your api key from apify") | |
| st.title("Fake Instagram Profile Detection") | |
| st.write("Plaese provide instagram account details you would like to predict") | |
| n = st.text_input("Enter username ") | |
| run_input = { "usernames": [n] } | |
| run = client.actor("dSCLg0C3YEZ83HzYX").call(run_input=run_input) | |
| m = client.dataset(run["defaultDatasetId"]) | |
| for item in m.iterate_items(): | |
| postsCount= item.get('postsCount') | |
| followersCount = item.get('followersCount') | |
| followsCount = item.get('followsCount') | |
| private=item.get('private') | |
| verified=item.get('verified') | |
| def predictor(postsCount,followersCount,followsCount,private,verified): | |
| prediction = model.predict([[postsCount,followersCount,followsCount,private,verified]]) | |
| print(prediction) | |
| return prediction | |
| if st.button("Predict"): | |
| result = predictor(postsCount,followersCount,followsCount,private,verified) | |
| st.write("The number of posts : " , postsCount) | |
| st.write("The number of followers : " ,followersCount) | |
| st.write("The number of following : " ,followsCount) | |
| st.write("Private : " ,private) | |
| st.write("Verified : " ,verified) | |
| if postsCount == None: | |
| st.error("The User Doesn't exist") | |
| elif result == 0 and postsCount != None: | |
| st.error("The Account is Likely to be Fake ") | |
| else: | |
| st.success("The Account is Likely to be Real") |