object detection

Introduction In the previous post, we ran a pre-trained YOLO26 model on street-level photographs from Rio de Janeiro, entirely in R. The model accepts exactly one input size, 640 × 640 pixels, so every photograph was shrunk to fit.

Introduction In an earlier post, we used a pre-trained YOLO model from R by reaching into Python with reticulate: import torch and ultralytics, hand a conda environment to use_condaenv(), and call the model as if it were an R object.

Introduction Object detection allows computers to identify and locate objects — like cars, people, street furniture — in images or videos. For urban planners, it offers a way to gather observational data at scale.