Create app.py

app.py

@@ -0,0 +1,93 @@
+import streamlit as st
+import numpy as np
+import pickle
+import streamlit.components.v1 as components
+from sklearn.preprocessing import LabelEncoder
+le = LabelEncoder()
+
+# Load the pickled model
+def load_model():
+    return pickle.load(open('Online_payment_fraud_detection_randomforest.pkl', 'rb'))
+
+# Function for model prediction
+def model_prediction(model, features):
+    predicted = str(model.predict(features)[0])
+    return predicted
+
+def transform(text):
+    text = le.fit_transform(text)
+    return text[0]
+
+
+def app_design():
+    # Add input fields for High, Open, and Low values
+    image = '26.png'
+    st.image(image, use_column_width=True)
+    
+    st.subheader("Enter the following values:")
+
+    step = st.number_input("Step")
+    typeup = st.text_input("Typeup")
+    typeup = transform([typeup])
+    amount = st.number_input("Amount")
+    nameOrig = st.text_input("NameOrig")
+    nameOrig = transform([nameOrig])
+    oldbalanceOrg = st.number_input("OldbalanceOrg")
+    newbalanceOrig = st.number_input("NewbalanceOrig")
+    nameDest = st.text_input("NameDest")
+    nameDest = transform([nameDest])
+    oldbalanceDest = st.number_input("OldbalanceDest")
+    newbalanceDest = st.number_input("NewbalanceDest")
+    isFlaggedFraud = st.number_input("IsFlaggedFraud")
+ 
+    # Create a feature list from the user inputs
+    features = [[step,typeup,amount,nameOrig,oldbalanceOrg,newbalanceOrig,nameDest,oldbalanceDest,newbalanceDest,isFlaggedFraud]]
+    
+    # Load the model
+    model = load_model()
+    
+    # Make a prediction when the user clicks the "Predict" button
+    if st.button('Predict Online Payment Fraud'):
+        predicted_value = model_prediction(model, features)
+        if predicted_value=='1':
+           st.success("Online payment fraud not happened")
+        else:
+           st.success("Online payment fraud happened")
+
+def about_hidevs():
+
+        components.html("""
+        <div>
+        <h4>🚀 Unlock Your Dream Job with HiDevs Community!</h4>
+        <p class="subtitle">🔍 Seeking the perfect job? HiDevs Community is your gateway to career success in the tech industry. Explore free expert courses, job-seeking support, and career transformation tips.</p>
+        <p class="subtitle">💼 We offer an upskill program in <b>Gen AI, Data Science, Machine Learning</b>, and assist startups in adopting <b>Gen AI</b> at minimal development costs.</p>
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+        <p class="subtitle">💡 Join us now, and turbocharge your career!</p>
+        <p class="subtitle"><a class="link" href="https://hidevscommunity.wixsite.com/hidevs" target="__blank">Website</a>
+        <a class="link" href="https://www.youtube.com/@HidevsCommunity1307/" target="__blank">YouTube</a>
+        <a class="link" href="https://www.instagram.com/hidevs_community/" target="__blank">Instagram</a>
+        <a class="link" href="https://medium.com/@hidevscommunity" target="__blank">Medium</a>
+        <a class="link" href="https://www.linkedin.com/company/hidevs-community/" target="__blank">LinkedIn</a>
+        <a class="link" href="https://github.com/hidevscommunity" target="__blank">GitHub</a></p>
+      </div>
+        """,
+                    height=600)
+
+def main():
+
+        # Set the app title and add your website name and logo
+        st.set_page_config(
+        page_title="Online Payment Fraud Detection",
+        page_icon=":chart_with_upwards_trend:",
+        )
+    
+        st.title("Welcome to our Online Paymment Fraud Detection App!")
+    
+        app_design()    
+        st.header("About HiDevs Community")
+        about_hidevs()
+
+if __name__ == '__main__':
+        main()