Image Deepfake Detection is a robust web application designed to detect manipulated images using convolutional neural networks (CNNs).
- User Authentication: Secure registration and login system for users.
- Image Upload: Users can upload images for analysis.
- CNN Analysis: Utilizes a pre-trained CNN model to analyze uploaded images.
- Comparison: Compares extracted features with a curated dataset.
- Classification: Determines whether the uploaded image is genuine or a deepfake.
- Result Visualization: Provides clear visual representation of the analysis results.
- Login: Log in with Goolge Oauth.
- Upload Image: Select an image file to upload for analysis.
- Analysis: Wait for the system to complete the analysis process.
- View Result: See the classification result indicating whether the uploaded image is genuine or a deepfake.
- Repeat: Continue analyzing additional images as needed.
Contributions to improve the application are encouraged. Feel free to submit pull requests or open issues in the GitHub repository to address any issues or suggest enhancements.
This project is developed for educational and research purposes and should not be solely relied upon for critical applications. While efforts have been made to provide accurate results, the system may have limitations and may not detect all deepfake images. It is recommended to employ multiple layers of verification for critical scenarios.
For inquiries, please contact [jeraldgolden00@gmail.com].