Unmanned Aerial Vehicle Imagery for Early Stage Weed Classification and Detection in Maize and Tomato Crops

The dataset, titled 'Unmanned Aerial Vehicle Imagery for Early Stage Weed Classification and Detection in Maize and Tomato Crops,' comprises RGB images captured from an unmanned aerial vehicle flying at an altitude of 11 meters. These images were taken during the early growing season of two summer crops: Maize (BBCH14) at the CSIC experimental farm La Poveda in Arganda del Rey, Madrid, Spain, and Tomato (BBCH501) in commercial plots located in Santa Amalia, Badajoz, Spain. The dataset includes 33,467 labels representing weeds (Atriplex patula, Chenopodium album, Convolvulus arvensis, Cyperus rotundus, Lolium rigidum, Portulaca oleracea, Salsola kali, Solanum nigrum) and crops (maize, tomato). All images are saved in *.jpg format and have been labeled using partitions extracted from an orthomosaic. The final result consists of a collection of individual images, each corresponding to a specific label, i.e., to each plant of each identified species.