ONNX Model Zoo

ninini1/AI-image-detector

By ninini1 · ↓ 2 · ♥ 1 · Updated 2024-08-25

What's in this repo

This page lists the files in ninini1/AI-image-detector, including AI-image-detector.onnx.

  • 1 ONNX models (.onnx files)
  • 6 files, including 2 .json, 1 .onnx, 1 .md, 1 .bin
  • Last updated 2024-08-25

ONNX files

File Size Download
AI-image-detector.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

NOTE: Unless you are trying to detect imagery generated using older models such as VQGAN+CLIP, please use the updated version of this detector instead.

This model is a proof-of-concept demonstration of using a ViT model to predict whether an artistic image was generated using AI.

It was created in October 2022, and as such, the training data did not include any samples generated by Midjourney 5, SDXL, or DALLE-3. It still may be able to correctly identify samples from these more recent models due to being trained on outputs of their predecessors.

Furthermore the intended scope of this tool is artistic images; that is to say, it is not a deepfake photo detector, and general computer imagery (webcams, screenshots, etc.) may throw it off.

In general, this tool can only serve as one of many potential indicators that an image was AI-generated. Images scoring as very probably artificial (e.g. 90% or higher) could be referred to a human expert for further investigation, if needed.

For more information please see the blog post describing this project at: https://medium.com/@matthewmaybe/can-an-ai-learn-to-identify-ai-art-545d9d6af226

Model Trained Using AutoTrain

  • Problem type: Binary Classification
  • Model ID: 1519658722
  • CO2 Emissions (in grams): 7.9405

Validation Metrics

  • Loss: 0.163
  • Accuracy: 0.942
  • Precision: 0.938
  • Recall: 0.978
  • AUC: 0.980
  • F1: 0.958

License Notice

This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.

You may distribute and make this model available to others as part of your own web page, app, or service so long as you provide attribution. However, use of this model within text-to-image systems to evade AI image detection would be considered a "derivative work" and as such prohibited by the license terms.

Model info

pytorch onnx swin autotrain vision image-classification license:cc-by-4.0 co2_eq_emissions region:us
↓ 2 ♥ 1

Created: 2024-08-25

Updated: 2024-08-25

View on Hugging Face

Files (6)

.gitattributes
AI-image-detector.onnx ONNX
README.md
config.json
preprocessor_config.json
pytorch_model.bin

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