Welcome to Scout

Wild Me’s Scout is designed to support processing aerial survey data taken from planes. Current machine learning is focused on supporting terrestrial surveys.

With Scout, you can:

  • Ingest high volumes of .ARW and .JPG images collected from survey cameras
  • Group images as “Tasks” that can be assigned to other users (e.g., image annotators) or machine learning (ML) models for bounding box creation and species labeling
  • Review and ground truth annotated images for accuracy
  • Draw division lines for overlapping image sequences with annotations
  • Export .CSV data files for statistical analysis

Who Should Read This Document

This documentation supports three Scout user roles:

  • System Administrators should be Linux- and computer hardware-savvy individuals who sets up Scout inside a lab. The System administrator’s primary functions are to install Linux on a powerful laptop, connect a network-attached storage (NAS) device to the laptop to hold high volumes of imagery, and install and run Scout via Docker. A system administrator verifies proper Scout installation and then communicates the URL to a lab lead to one or more lab leads.
  • Lab Leads connect to Scout through a Chrome web browser and EW responsible for creating and managing user accounts, coordinating work (e.g., assigning groups of images as Tasks to annotators or (ML models), reviewing annotator work to create final “ground truth” annotations, drawing division lines to specify overlap in imagery with annotated animals, and exporting data for analysis in third party applications.
  • Annotators log into Scout through a Chrome web browser and receives tasks to annotate from lab leads. An annotator is responsible for drawing and labeling bounding boxes on each image, with each bounding box representing an occurrence of a single animal or other supported classification found in an image.