01 Synopsis
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- PDF & Word both included
- Up to 30 pages
- Only 1 diagram included
- Problem statement & objectives
- Ready for college submission
Complete final-year project report with documentation, diagrams and viva-ready structure. Instant PDF & Word download — plagiarism-free and faculty-aligned.
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01 Synopsis
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02 Pre Defined Project Report
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03 Customized Report
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04 Originality Reviewed
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Abstract
Table of Content
Introduction
Problem Statement
Existing System
Proposed System
Objectives
System Architecture
Major Functional Modules
Hardware Requirements
Software Requirements
Future Enhancement
Conclusion
References
Abstract
Table of Content
Chapter 1 — Introduction
Chapter 2 — Literature Review / System Study
Chapter 3 — System Analysis
Chapter 4 — System Design
Chapter 5 — System Implementation
Chapter 6 — Testing
Chapter 7 — Results and Discussion
Chapter 8 — Conclusion and Future Enhancements
Chapter 9 — References
Deepfake Detection Using Machine Learning is a Python Flask based final year project developed for detecting deepfake images and videos using machine learning. This major project includes a public landing page, user dashboard, and admin dashboard. Users can register, log in, upload images, upload videos, run deepfake detection, view real/fake predictions, check confidence scores, view frame-wise video analysis, download PDF or TXT reports, manage detection history, update profile details, change password, and securely log out. Admins can monitor total users, total detections, real media count, deepfake count, failed detections, recent users, all detection records, and user accounts. The detection pipeline uses OpenCV face detection, feature extraction, Xception + LSTM machine learning model prediction, and local processing without third-party APIs. This deepfake detection source code is suitable for students who need a final year project, major project, minor project, source code, and project report based on Python, Flask, TensorFlow, Keras, OpenCV, and machine learning.
Admin Account
[email protected]adminadmin123/admin/Sample User Accounts
All sample users use password:
password123
Sample users:
johnsmith — Email: [email protected]sarahj — Email: [email protected]mikebrown — Email: [email protected]emilyd — Email: [email protected]davidw — Email: [email protected]lisaanderson — Email: [email protected]jamest — Email: [email protected]mariag — Email: [email protected]Open project folder:
cd "Deepfake Detection Using Machine Learning"
Create virtual environment:
python -m venv venv
Activate virtual environment on Windows:
venv\Scripts\activate
Activate virtual environment on Linux/macOS:
source venv/bin/activate
Install dependencies:
pip install -r requirements.txt
Place trained ML model weights file:
ml_models/deepfake_model.weights.h5
Seed the database:
python seed.py
Start the application:
python app.py
http://localhost:5000
Most Important - Download the Pre Trained Model File from here.
Admin Account
[email protected]adminadmin123/admin/Sample User Accounts
All sample users use password:
password123
Sample users:
johnsmith — Email: [email protected]sarahj — Email: [email protected]mikebrown — Email: [email protected]emilyd — Email: [email protected]davidw — Email: [email protected]lisaanderson — Email: [email protected]jamest — Email: [email protected]mariag — Email: [email protected]