DeepfakeWeedSet

[Description of methods used for collection/generation of data] The artificial weed imagery contained in the DeepfakeWeedSet (_1 and _2) was generated using Stable Diffusion, a modern generative AI model that was conditioned with a set of real field images from Moreno et al. (2025). These real images depicted weed species naturally occurring in tomato crops, specifically Solanum nigrum, Portulaca oleracea, and Setaria verticillata. They served as the visual foundation from which Stable Diffusion learned the characteristic shapes, colors, and textures of each weed species. Once this reference material was provided, Stable Diffusion was used to synthesize thousands of new, highly realistic images, resulting in an artificial dataset comprising 10,800 synthetic images that include a total of 12,592 annotated weed instances (i.e., bounding boxes). References Hugo Moreno, Gabriel Rivera, Dionisio Andújar. Ground-based imagery dataset for early weed classification in tomato crops,Data in Brief. Volume 63,2025,112249,ISSN 2352-3409,https://doi.org/10.1016/j.dib.2025.112249.