Abstract
The recent changes in policies in several countries regarding cannabis use has increased cannabis usage and research [1,2]. Cannabis is the second most used psychoactive substance word-wide [3]. Cannabis remains the subject of many research works. The cannabis can be classified into different classes according to their external features like colour, shape, and size using some computer vision and machine learning techniques. Precise classification or recognition is the unmet need of the agriculture business. This attracts many researchers to produce solutions with machine learning and deep learning techniques. Neat and clean dataset is the primary requirements to build accurate and robust machine learning model and minimize misclassification for the real-time environment. To achieve this objective, we have created an image dataset of cannabis seed. Accordingly, we have considered seventeen cannabis seeds to create dataset. The dataset contains 17 subfolders of cannabis seeds and folder is named with the category of seed. We strongly believe the cannabis seeds dataset will be very helpful for training, testing, and validation of cannabis classification or recognition with machine learning models.