Evaluate image models in their detection of real vs fake images of people. Details about these models will be provided after more testing is performed:
- Model-1: This model is an image classifier that generates real vs fake scores. No explanations are provided.
- Model-2: This model is an image classifier that generates real vs fake scores. No explanations are provided.
- Model-3: This model is an image classifier that generates human vs artificial scores. No explanations are provided.
- Model-4: This model is an LLM vision model that generates real vs fake scores as well as explanations.
These tests use the Roboflow Image Detection (Rake & Real) Dataset v1. Note that other image datasets, such as the Kaggle 140k Real and Fake Faces dataset may be considered for future tests.
- Randomly select a sample set of real and fake images to serve as the test dataset.
- For each image in test dataset, run the image through each model and generate real and fake scores for the image. Compare these scores against the actual type for the image (Real vs Fake). If the model correctly identifies the type, the result is 'Pass'.
- Compute the accuracy for each model over the test dataset.
Short test with 10 images. Note that the prompt for Model-4 is still being refined to improve accuracy and explanations.
Results Overview
Model 1:
- Pass: 80%
Model 2:
- Pass: 80%
Model 3:
- Pass: 100%
Model 4:
- Pass: 60%
Note that an LLM vision model could potentially be used to provide explanations for another model that exhibits high accuracy but does not provide explanations. For example, we see that Model-3 has accurately identified all images in the dataset but does not provide explanations. Here, we can use the results from Model-3 to inform an LLM vision model, Model-4, that an image has been determined to be Real or Fake, and then instruct Model-4 to explain why. This is shown below for Image #6 where Model-3 accurately identifies the image as fake.
Note here that Model-4's explanation for why the image is fake is different from its previous explanation of why the image is real. Further note that Model-4 provides its own reasoning for why an image may be real or fake and does not have insight into the reasoning of Model-3.