Subject	Agronomy and Crop Science, Computer Vision and Pattern Recognition.
Specific subject area	Object classification, Object detection, Object recognition, Crop growth and development.
Type of data	Image. Annotations.
How data were acquired	The data was acquired by capturing images with a resolution of 720 × 1280 × 3, 1000 × 750 × 3, 640 × 480 × 3, 640 × 360 × 3 and 480 × 384 × 3 pixels in a controlled and unregulated environment using the Canon EOS 800D, and Sony W800 digital cameras and the Intel RealSense D435 camera. Images were manually annotated by using software importing: python os, cv2, sys, xml.etree.ElementTree.
Data format	Raw images:.jpg format, manually annotated images: .xml files
Parameters for data collection	Data was acquired by capturing images in field conditions and in a controlled environment.
Description of data collection	Dataset consists of two directories. Directory images) 1118 food crops and weed images and directory annotations, i.e. their 1118 counterpart annotation XML files, which can be included 7853 annotations of two classes: food crops (six species), 441 annotations and weed (eight species), 7442 annotations.
Data source location	Municipalities: •Jelgava (controlled environment) •Ķekava parish (open field) •Rūjiena parish (open field) •Krimulda parish (open field) •Country: Latvia
Data accessibility	With an article