Automatic Crop Seed Counting Method Based on YOLOX Model

Seed counting is the most critical and tedious step in acquisition of kilograin weight index of crop seeds．At present, seed counting is generally achieved by manual and specialized equipment．But manual counting efficiency is low and specialized equipment are expensive and not easy to carry．Datasets were constructed using images of six different common crop seeds taken by mobile phone．Based on YOLOX model, attention mechanism was introduced and loss function was improved to obtain the YOLOX-P model, which realized automatic counting of seeds．Results showed that YOLOX-P only increased 0.09 M compared with YOLOX model parameters, mAP improved 0.74 percentage points and reached 99.38%．Reasoning time of the model on NVIDIA GeForce RTX 2060 graphics card with 6 GB video memory was 18.68 ms, which was suitable for deployment on the mobile , and significantly improves efficiency and effect of measuring kilograin weight．