Added dashboard and requirements

dashboard.py

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+import gradio as gr
+import sqlite3
+import re
+import bcrypt
+import numpy as np
+import cv2
+from PIL import Image
+import tensorflow as tf
+import os
+import warnings
+
+# Suppress all warnings
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+warnings.filterwarnings("ignore")
+np.seterr(all='ignore')
+
+# Load model
+deepfake_model = tf.keras.models.load_model("model_15_64 (1).h5")
+
+# Setup SQLite instead of MySQL
+conn = sqlite3.connect("users.db", check_same_thread=False)
+cursor = conn.cursor()
+
+# Create user_details table in SQLite
+cursor.execute('''
+CREATE TABLE IF NOT EXISTS user_details (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    NAME TEXT,
+    PHONE TEXT,
+    EMAIL TEXT UNIQUE,
+    GENDER TEXT,
+    PASSWORD TEXT
+)
+''')
+conn.commit()
+
+# Validation utilities
+def is_valid_email(email):
+    return re.match(r"[^@]+@[^@]+\.[^@]+", email)
+
+def is_valid_phone(phone):
+    return re.match(r"^[0-9]{10}$", phone)
+
+def preprocess_image(image):
+    image = np.array(image)
+    image = cv2.resize(image, (128, 128))
+    image = image.astype(np.float32) / 255.0
+    return np.expand_dims(image, axis=0)
+
+def predict_image(image):
+    preprocessed = preprocess_image(image)
+    prediction = deepfake_model.predict(preprocessed)[0][0]
+    return "✅ Real Image" if prediction >= 0.5 else "⚠️ Fake Image"
+
+# Register user
+def register_user(name, phone, email, password):
+    if not is_valid_email(email):
+        return "❌ Invalid email", False
+    if not is_valid_phone(phone):
+        return "❌ Phone must be 10 digits", False
+
+    cursor.execute("SELECT * FROM user_details WHERE EMAIL = ?", (email,))
+    if cursor.fetchone():
+        return "⚠️ Email already registered", False
+
+    hashed_pw = bcrypt.hashpw(password.encode(), bcrypt.gensalt())
+    cursor.execute("INSERT INTO user_details (NAME, PHONE, EMAIL, GENDER, PASSWORD) VALUES (?, ?, ?, ?, ?)",
+                   (name, phone, email, "U", hashed_pw))
+    conn.commit()
+    return "✅ Registration successful! Please log in.", True
+
+# Login user
+def login_user(email, password):
+    cursor.execute("SELECT PASSWORD FROM user_details WHERE EMAIL = ?", (email,))
+    result = cursor.fetchone()
+    if result and bcrypt.checkpw(password.encode(), result[0].encode() if isinstance(result[0], str) else result[0]):
+        return "✅ Login successful!", True
+    return "❌ Invalid credentials", False
+
+# App layout
+with gr.Blocks() as demo:
+    session = gr.State({})
+    show_login = gr.State(True)
+
+    status = gr.Textbox(label="", interactive=False)
+
+    with gr.Column(visible=True) as login_panel:
+        gr.Markdown("### Login or Sign Up")
+        name = gr.Textbox(label="Name (Sign Up Only)")
+        phone = gr.Textbox(label="Phone (Sign Up Only)")
+        email = gr.Textbox(label="Email")
+        password = gr.Textbox(label="Password", type="password")
+
+        login_btn = gr.Button("Login")
+        signup_btn = gr.Button("Sign Up")
+
+    with gr.Column(visible=False) as prediction_panel:
+        gr.Markdown("## Upload Image for Deepfake Detection")
+        image_input = gr.Image(type="pil")
+        result = gr.Textbox(label="Result")
+        predict_btn = gr.Button("Predict")
+        logout_btn = gr.Button("Logout")
+
+    # Logic
+    def handle_login(e, p):
+        msg, ok = login_user(e, p)
+        return msg, gr.update(visible=not ok), gr.update(visible=ok)
+
+    def handle_signup(n, ph, e, p):
+        msg, ok = register_user(n, ph, e, p)
+        return msg
+
+    def handle_logout():
+        return {}, gr.update(visible=True), gr.update(visible=False)
+
+    login_btn.click(handle_login, [email, password], [status, login_panel, prediction_panel])
+    signup_btn.click(handle_signup, [name, phone, email, password], status)
+    predict_btn.click(predict_image, inputs=image_input, outputs=result)
+    logout_btn.click(handle_logout, outputs=[session, login_panel, prediction_panel])
+
+# Launch
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+tensorflow
+opencv-python
+Pillow
+bcrypt
+numpy