WildObs is developing computer vision (CV) models tailored to Australian species and environments to support accurate, scalable annotation of wildlife camera trap images. Training accurate models requires curated datasets of tagged images. 

Ideally, all legacy data should be submitted in preferred formats as described in the Submit your data guide. 

If you do not have the resources to submit data in the preferred format and have been invited to submit data for CV model training by the WildObs team, please use the following minimal guide. 

Submit data for CV model training

Steps in this guide:

• Step 1: Image file name and location.

• Step 2: Prepare a spread sheet of basic information.

• Step 3: Send your data.

Step 1: Image file name and location.

• Each image should have a unique image ID as it's file name.
• Images should be stored in a shared cloud storage location (OneDrive, Google Drive, Azure, Dropbox) or can be sent via FileSender

Step 2: Prepare a spread sheet of basic information.

• Prepare a spread sheet with the following columns, with each image as a row:
  • mediaID - Unique file name for each camera trap image. 
  • filePath - Relative path to the image in the shared directory or a URL link directly to the image in cloud storage.
  • scientificName - Scientific name for the species identified in the camera trap image. 
  • taxonRank - Taxonomic rank of the most specific scientific name (e.g. species, genus, family, class).

• If you cannot prepare a spread sheet with the above details, alternatives include:
  • Shared directory of cloud storage location has a descriptive file naming system.
  • Species name included in the file name.

Please provide advice in your submission describing the naming system used. 

Step 3: Send your data. 

• Email support@wildobs.org.au with your image share link and spread sheet, or details of your naming system.