Digital hemispherical photography (i.e., hemiphoto) is a convenient, rapid tool to estimate two key canopy structure parameters: leaf area index (LAI) and leaf angle distribution (LAD). Underlying such use of hemiphotos is a gap probability model widely known as either the Poisson model or Beer's Law for describing light-vegetation interactions. Based on this gap formula, numerous algorithms have been developed to convert hemiphotos into LAI and LAD. The hemiphoto2LAI package implements a total of 135 LAI estimation models, including the majority of classical algorithms proposed during the past several decades and more importantly, a newly proposed binary nonlinear regression algorithm (BNR). The implemented algorithms are adopted to a total of 19 common leaf angle distribution models. Details on the BNR algorithm and the package can be found in Zhao et al. (2019).