This model was trained on a large number of iNaturalist observations with species detected in Singapore. Our class list is derived from GBIF observations in Singapore, plus additional classes taken from the Singapore NParks website.

For usage, see "spaces using this model".

All imagery was taken from https://github.com/inaturalist/inaturalist-open-data.

In principle we release our models as CC-BY-4.0. The licensing for source images have various flavours of CC.

We used this model in the XPrize competition, but if you wish to use the model for other applications you may need to retrain the model on images with licenses appropriate for your use-case. Do not assume that you can use this model for commercial applications.

This model performs well on fauna, but less well on flora. Plant species are hard to identify automatically and many require multiple viewpoints to identify unambiguously.
{"license": "cc-by-4.0"}
license:cc-by-4.0 has_space region:us
TAGS
#license-cc-by-4.0 #has_space #region-us 

This model was trained on a large number of iNaturalist observations with species detected in Singapore. Our class list is derived from GBIF observations in Singapore, plus additional classes taken from the Singapore NParks website.

For usage, see "spaces using this model".

All imagery was taken from URL

In principle we release our models as CC-BY-4.0. The licensing for source images have various flavours of CC.

We used this model in the XPrize competition, but if you wish to use the model for other applications you may need to retrain the model on images with licenses appropriate for your use-case. Do not assume that you can use this model for commercial applications.

This model performs well on fauna, but less well on flora. Plant species are hard to identify automatically and many require multiple viewpoints to identify unambiguously.
TAGS
#license-cc-by-4.0 #has_space #region-us 
