Percept-Lens Evaluation Data - Ideogram-75k

<p><strong>Percept-Lens-Ideogram-75k Dataset Description</strong></p>

<p><strong>Purpose.</strong><br>
The Percept-Lens-Ideogram-75k dataset is curated as part of the <em>Percept-Lens</em> benchmark to evaluate the generalization capability of AI-generated image detectors under prompt-induced distribution shifts. It serves as an out-of-distribution (OOD) test set, designed to probe model robustness against semantically rich prompts not seen during training.</p>

<p><strong>Nature.</strong><br>
This dataset contains only AI-generated images created from text prompts sourced from the Ideogram-75k Dataset. These prompts span abstract concepts, visual reasoning, compositional scenes, and imaginative queries. Images were generated using diverse diffusion models, including <em>Stable Diffusion variants</em>, and <em>FLUX.variants</em>, ensuring stylistic variation. No real images are included—each image is the synthetic output of a generative model responding to a high-level prompt.</p>

<p><strong>Scope.</strong><br>
The dataset includes approximately 1,275,357 images, with each image linked to its original prompt. It is used exclusively for evaluation within the Percept-Lens benchmark and is not part of the training data. This subset is particularly useful for testing <em>semantic generalization</em>, where linguistic complexity drives visual synthesis beyond familiar domains.