This dataset contains 46,843 raw, expert-confirmed seed/bean images covering 13 locally recognised varieties across three economically important Ghanaian crops: cocoa (4 varieties — Agric, Gardener, Hybrid, Tetteh Quarshie; 3,323 images), maize (5 varieties — Bhihilifa, Obaatampa, Sanzal Sima, Wang Basik, Wang Dataa; 25,696 images), and soybean (4 varieties — Afayak, FarmerSaved, Favor, Tenguma; 17,824 images). Maize and soybean seeds were pre-sorted by variety at Heritage Seeds Ghana; cocoa seeds were extracted from pods pre-sorted by variety by farm experts in Berekum, Ghana, and sun-dried for seven days before imaging. All seeds were photographed in groups on a plain background with a Google Pixel 9a smartphone, then cropped into individual seed images, with variety labels confirmed throughout by the respective experts. Images are resized to 224 × 224 px and organised into folders by crop and variety. The dataset supports development of low-cost, mobile deep-learning models for seed variety identification and certification, addressing the current lack of openly available, cultivar-labelled image data for African seed crops. Class distributions are close to balanced, though a few varieties (e.g., Agric cocoa, Obaatampa maize) are comparatively under-represented