Email_Classification/app.py at main · MuhammadSamarShehzad/Email_Classification · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
import streamlit as st
import joblib
import numpy as np

# -------------------- Page Config --------------------
st.set_page_config(page_title="Spam Email Detector", page_icon="📧", layout="wide")

# -------------------- Styles (High Contrast, Vibrant) --------------------
st.markdown("""
<style>
/* Global background and font */
html, body, [data-testid="stAppViewContainer"]{
  background: #f3f4f6;
  color: #111827;
  font-family: 'Inter', sans-serif;
}

/* Centered header */
.header-title {
  text-align: center;
  font-size: 3rem;
  font-weight: 900;
  color: #1e40af;
  margin-bottom: 0.25rem;
}
.sub {
  text-align: center;
  color: #4b5563;
  margin-bottom: 2rem;
  font-size: 1.1rem;
}

/* Card design */
.card {
  background: white;
  border-radius: 16px;
  padding: 1.5rem 1.25rem;
  box-shadow: 0 8px 24px rgba(0, 0, 0, 0.08);
  border: 1px solid #e5e7eb;
}

/* Textarea */
.stTextArea textarea {
  background: white !important;
  color: #111827 !important;
  border-radius: 12px !important;
  border: 1px solid #cbd5e1 !important;
  font-size: 1rem !important;
  padding: 12px !important;
}

/* Predict button */
.stButton>button {
  background: linear-gradient(135deg, #2563eb, #1e40af);
  color: #fff;
  font-size: 1.1rem;
  font-weight: 600;
  padding: 0.75rem 1.5rem;
  border: none;
  border-radius: 10px;
  transition: 0.2s ease;
  box-shadow: 0 6px 18px rgba(37, 99, 235, 0.3);
}
.stButton>button:hover {
  background: linear-gradient(135deg, #1e3a8a, #1e40af);
  transform: translateY(-2px);
}

/* Result badges */
.badge {
  display:inline-block;
  padding: .4rem .85rem;
  border-radius: 9999px;
  font-weight: 600;
  color: white;
  margin-bottom: 1rem;
  font-size: .95rem;
}
.badge.spam { background: #dc2626; }
.badge.ham { background: #16a34a; }

/* Footer */
footer, .viewerBadge_container__1QSob, .stDeployButton { display:none !important; }
.footer {
  margin-top: 2rem;
  text-align: center;
  color: #6b7280;
  font-size: .9rem;
}
</style>
""", unsafe_allow_html=True)

# -------------------- Load Model --------------------
@st.cache_resource
def load_artifacts():
    model = joblib.load("spam_detector_model.pkl")
    vectorizer = joblib.load("vectorizer.pkl")
    return model, vectorizer

model, vectorizer = load_artifacts()

# -------------------- Header --------------------
st.markdown('<div class="header-title">📧 Spam Email Detector</div>', unsafe_allow_html=True)
st.markdown('<div class="sub">Paste your email content and classify it as <strong>Spam</strong> or <strong>Not Spam</strong>.</div>', unsafe_allow_html=True)

# -------------------- Input --------------------
with st.container():
    st.markdown('<div class="card">', unsafe_allow_html=True)
    email_text = st.text_area("Email content:", height=200, placeholder="Paste the email body here...")
    predict = st.button("Predict 🔍")
    st.markdown('</div>', unsafe_allow_html=True)

# -------------------- Prediction --------------------
if predict:
    if not email_text.strip():
        st.error("Please enter an email message to classify.")
    else:
        email_vector = vectorizer.transform([email_text])
        pred = model.predict(email_vector)[0]
        proba = model.predict_proba(email_vector)[0] if hasattr(model, "predict_proba") else [1, 0] if pred == 0 else [0, 1]

        spam_prob = proba[1] * 100
        ham_prob = proba[0] * 100

        # Result Card
        st.markdown('<div class="card">', unsafe_allow_html=True)
        if pred == 1:
            st.markdown('<span class="badge spam">🚨 Spam Detected</span>', unsafe_allow_html=True)
            st.write(f"### This email is **Spam** (Probability: **{spam_prob:.2f}%**)")
            st.progress(int(spam_prob))
        else:
            st.markdown('<span class="badge ham">✅ Not Spam</span>', unsafe_allow_html=True)
            st.write(f"### This email is **Safe** (Probability: **{ham_prob:.2f}%**)")
            st.progress(int(ham_prob))

        col1, col2 = st.columns(2)
        with col1:
            st.metric("Ham Probability", f"{ham_prob:.2f}%")
        with col2:
            st.metric("Spam Probability", f"{spam_prob:.2f}%")
        st.markdown('</div>', unsafe_allow_html=True)

# -------------------- Footer --------------------
st.markdown('<div class="footer">© 2025 • Spam Email Detector</div>', unsafe_allow_html=True)