fardinabbasi/ML_Fake_Image_Detection

Detecting fake images using machine learning, involving feature extraction from real and AI-generated images, and implementing various classification models such as Random Forest, SVM, and Logistic Regression to accurately distinguish between real and fake images.

21
/ 100
Experimental

This project helps identify whether an image is real or generated by AI, such as Stable Diffusion or DALL.E. You provide a collection of images, and it outputs a classification indicating if each image is 'real' or 'fake'. This is ideal for content moderators, journalists, or anyone needing to verify the authenticity of images.

No commits in the last 6 months.

Use this if you need to automatically detect AI-generated images within a large dataset, particularly for natural scenes like seas, mountains, and jungles.

Not ideal if you need to detect manipulated real images or identify deepfakes of human faces, as its focus is on distinguishing purely AI-generated scenic images from real ones.

image-verification content-moderation digital-forensics media-authenticity AI-content-detection
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 8 / 25

How are scores calculated?

Stars

9

Forks

1

Language

Jupyter Notebook

License

Last pushed

Aug 13, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/fardinabbasi/ML_Fake_Image_Detection"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.