Update fpd1.py
Browse files
fpd1.py
CHANGED
@@ -1,39 +1,39 @@
|
|
1 |
-
import numpy as np
|
2 |
-
import pandas as pd
|
3 |
-
import streamlit as st
|
4 |
-
import joblib
|
5 |
-
from apify_client import ApifyClient
|
6 |
-
model = joblib.load("classifier.pkl")
|
7 |
-
client = ApifyClient("
|
8 |
-
st.title("Fake Instagram Profile Detection")
|
9 |
-
st.write("Plaese provide instagram account details you would like to predict")
|
10 |
-
n = st.text_input("Enter username ")
|
11 |
-
run_input = { "usernames": [n] }
|
12 |
-
run = client.actor("dSCLg0C3YEZ83HzYX").call(run_input=run_input)
|
13 |
-
m = client.dataset(run["defaultDatasetId"])
|
14 |
-
for item in m.iterate_items():
|
15 |
-
postsCount= item.get('postsCount')
|
16 |
-
followersCount = item.get('followersCount')
|
17 |
-
followsCount = item.get('followsCount')
|
18 |
-
private=item.get('private')
|
19 |
-
verified=item.get('verified')
|
20 |
-
|
21 |
-
def predictor(postsCount,followersCount,followsCount,private,verified):
|
22 |
-
prediction = model.predict([[postsCount,followersCount,followsCount,private,verified]])
|
23 |
-
print(prediction)
|
24 |
-
return prediction
|
25 |
-
|
26 |
-
|
27 |
-
if st.button("Predict"):
|
28 |
-
result = predictor(postsCount,followersCount,followsCount,private,verified)
|
29 |
-
st.write("The number of posts : " , postsCount)
|
30 |
-
st.write("The number of followers : " ,followersCount)
|
31 |
-
st.write("The number of following : " ,followsCount)
|
32 |
-
st.write("Private : " ,private)
|
33 |
-
st.write("Verified : " ,verified)
|
34 |
-
if postsCount == None:
|
35 |
-
st.error("The User Doesn't exist")
|
36 |
-
elif result == 0 and postsCount != None:
|
37 |
-
st.error("The Account is Likely to be Fake ")
|
38 |
-
else:
|
39 |
st.success("The Account is Likely to be Real")
|
|
|
1 |
+
import numpy as np
|
2 |
+
import pandas as pd
|
3 |
+
import streamlit as st
|
4 |
+
import joblib
|
5 |
+
from apify_client import ApifyClient
|
6 |
+
model = joblib.load("classifier.pkl")
|
7 |
+
client = ApifyClient("your api key from apify")
|
8 |
+
st.title("Fake Instagram Profile Detection")
|
9 |
+
st.write("Plaese provide instagram account details you would like to predict")
|
10 |
+
n = st.text_input("Enter username ")
|
11 |
+
run_input = { "usernames": [n] }
|
12 |
+
run = client.actor("dSCLg0C3YEZ83HzYX").call(run_input=run_input)
|
13 |
+
m = client.dataset(run["defaultDatasetId"])
|
14 |
+
for item in m.iterate_items():
|
15 |
+
postsCount= item.get('postsCount')
|
16 |
+
followersCount = item.get('followersCount')
|
17 |
+
followsCount = item.get('followsCount')
|
18 |
+
private=item.get('private')
|
19 |
+
verified=item.get('verified')
|
20 |
+
|
21 |
+
def predictor(postsCount,followersCount,followsCount,private,verified):
|
22 |
+
prediction = model.predict([[postsCount,followersCount,followsCount,private,verified]])
|
23 |
+
print(prediction)
|
24 |
+
return prediction
|
25 |
+
|
26 |
+
|
27 |
+
if st.button("Predict"):
|
28 |
+
result = predictor(postsCount,followersCount,followsCount,private,verified)
|
29 |
+
st.write("The number of posts : " , postsCount)
|
30 |
+
st.write("The number of followers : " ,followersCount)
|
31 |
+
st.write("The number of following : " ,followsCount)
|
32 |
+
st.write("Private : " ,private)
|
33 |
+
st.write("Verified : " ,verified)
|
34 |
+
if postsCount == None:
|
35 |
+
st.error("The User Doesn't exist")
|
36 |
+
elif result == 0 and postsCount != None:
|
37 |
+
st.error("The Account is Likely to be Fake ")
|
38 |
+
else:
|
39 |
st.success("The Account is Likely to be Real")
|