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DeepFake_Detector

Building a deep fake image detection model that is capable of classifying images into two categories Ai-Generated or Real images using TensorFlow

Problem Definition

  • The model is used for the detection of deep fake or AI-generated images that are now widely used for spreading hate speech and fake news.

Data

*We are using Kaggle data uploaded on the drive can be downloaded from the following URL https://www.kaggle.com/datasets/ericji150/nsf-reu-2023-sd-21 [E. Ji, B. Dong, B. Samanthula, N. Zhou. "2D-FACT: Dual-Domain Fake Image Detection Against Textto-Image Generative Models". MIT Undergraduate Research Technology Conference (URTC 2023).]

  • For the Training dataset our project includes 10,000 Fake and 10,000 Real images which can create a bias so our project acknowledges these issues by reducing the number of fake images without affecting the accuracy largely

Evaluation

Features

  • A few key information about features as the project is based on unstructured image classification, Thus there is no such distinctive feature but the data is divided into 3 parts. Testing, Training, and Validation. the model will be a binary classifier

# for unzipping the zip file run this #!unzip '/content/drive/MyDrive/Deepfake/deepfake.zip' -d "/content/drive/MyDrive/Deepfake/"

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