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DeepFake Image Detection System Using Deep Learning
Computer VisionThis project is a DeepFake Image Detection System that uses deep learning and computer vision techniques to identify whether an uploaded image is real or fake. A trained Convolutional Neural Network (CNN) model analyzes facial and image patterns to detect manipulations commonly found in deepfake content. The system is deployed as a Flask-based web application, allowing users to upload images through a simple interface. Uploaded images are preprocessed using OpenCV, resized, normalized, and passed to the trained model for prediction. The application outputs the classification result (REAL or FAKE) along with a confidence score, making the detection process transparent and user-friendly. This project helps address the growing concern of digital misinformation by providing an automated and efficient solution for deepfake detection.