| 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") |
