EasyRFP: An Easy to Use Edge Computing Toolkit for Real-Time Field Phenotyping
Akshay L Chandra*, Sai Vikas Desai*, Hirafuji Masayuki, Seishi Ninomiya, Vineeth N Balasubramanian, and Wei. Guo
Extended Abstract at CVPPP & ECCV Academic Demonstrations, Aug 2020
We propose EasyRFP, an edge computing toolkit for real-time field phenotyping. Recent advances in deep learning have catalysed rapid progress in high throughput field phenotyping. Much research has been dedicated towards developing accurate and cost effective deep learning models to capture phenotyping traits such as plant stress, yield and plant growth stages. However, there is a shortage of software tools to promote the usage of such intelligent methods among plant phenotyping practitioners and researchers. To bridge this gap, we developed this, a Flask backend, Angular frontend software toolkit. Broadly speaking, our toolkit can be interfaced with a commercial GPU enabled micro computer (such as NVIDIA Jetson) and a digital camera. Precisely, our toolkit can be used to capture images and extract phenotypic traits in both real-time and in scheduled mode. Currently, we support classification, detection and instance segmentation tasks.