SpeciesNet 4.0.1 Docker images available
First Docker images are available for the SpeciesNet network that Google announced on March 3rd, 2025:
Below is an example on how to use these images (on Linux or on Windows under WSL2).
Prerequisites:
create a directory for your output eg "speciesnet"
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in that directory create the following sub-directories
cache
config
data
output
Processing data:
copy the images that you want to analyze into the "speciesnet/data" directory
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from the "speciesnet" directory launch the appropriate docker image in interactive mode
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CPU:
docker run --rm --gpus=all --shm-size 8G --net=host \ -u $(id -u):$(id -g) -e USER=$USER \ -v `pwd`:/workspace \ -v `pwd`/cache:/.cache \ -v `pwd`/config:/.config \ -v `pwd`/cache:/.torch \ -it waikatodatamining/speciesnet:4.0.1_cpu
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CUDA:
docker run --rm --gpus=all --shm-size 8G --net=host \ -u $(id -u):$(id -g) -e USER=$USER \ -v `pwd`:/workspace \ -v `pwd`/cache:/.cache \ -v `pwd`/config:/.config \ -v `pwd`/cache:/.torch \ -it waikatodatamining/speciesnet:4.0.1_cuda21.1
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run the following script to process your images:
speciesnet_run_model \ --folders "/workspace/data" \ --predictions_json "/workspace/output/predictions.json"
Or, if you want to run the individual steps separately:
speciesnet_run_model --detector_only \
--folders "/workspace/data" \
--predictions_json "/workspace/output/detections.json"
speciesnet_run_model --classifier_only \
--folders "/workspace/data" \
--detections_json "/workspace/output/detections.json" \
--predictions_json "/workspace/output/classifications.json"
speciesnet_run_model --ensemble_only \
--folders "/workspace/data" \
--detections_json "/workspace/output/detections.json" \
--classifications_json "/workspace/output/classifications.json" \
--predictions_json "/workspace/output/predictions.json"
On your host system, the "speciesnet/output" directory will then contain the generated .json file(s), with "predictions.json" containing all the relevant information (classification and bbox).
For more information on the json output format:
https://github.com/google/cameratrapai/tree/main?tab=readme-ov-file#output-format