This is a species classification model for camera trap images to identify 30 species or higher level taxons present in the Skeleton Coast National Park. The model was trained on a set of more than 850,000 images. The classification model has an overall validation accuracy of 95.3%, a precision of 95.4%, and a recall of 95.3%. It is designed to be used in conjunction with MegaDetector as a feature extractor. This pipeline is integrated into the open-source camera trap analysis software EcoAssist.
More info on the model: https://addaxdatascience.com/projects/2023-01-dlc/
| Class | Precision | Recall | Accuracy |
|---|---|---|---|
| aardwolf | 84.9% | 93.5% | 89.0% |
| african wild cat | 98.9% | 98.5% | 98.7% |
| baboon | 93.9% | 96.5% | 95.2% |
| bird | 92.1% | 92.9% | 92.5% |
| brown hyaena | 96.3% | 97.6% | 97.0% |
| caracal | 75.0% | 85.7% | 80.0% |
| cattle | 96.2% | 99.1% | 97.6% |
| cheetah | 88.8% | 95.9% | 92.2% |
| donkey | 93.0% | 67.7% | 78.4% |
| elephant | 97.3% | 95.5% | 96.4% |
| fox | 80.4% | 77.4% | 78.9% |
| gemsbok | 94.4% | 96.1% | 95.3% |
| genet | 87.5% | 50.0% | 63.6% |
| giraffe | 97.5% | 96.9% | 97.2% |
| hare | 98.6% | 97.5% | 98.0% |
| honey badger | 70.7% | 78.4% | 74.4% |
| hyrax | 94.1% | 100.0% | 97.0% |
| jackal | 83.5% | 90.5% | 86.9% |
| klipspringer | 77.8% | 93.3% | 84.8% |
| kudu | 90.8% | 98.8% | 94.6% |
| leopard | 93.4% | 81.4% | 87.0% |
| lion | 96.8% | 96.6% | 96.7% |
| mongoose | 76.5% | 89.5% | 82.5% |
| ostrich | 92.9% | 94.9% | 93.9% |
| porcupine | 98.0% | 96.5% | 97.2% |
| rhinoceros | 89.1% | 94.8% | 91.9% |
| spotted hyaena | 96.4% | 92.9% | 94.6% |
| springbok | 91.5% | 90.3% | 90.9% |
| steenbok | 85.7% | 95.0% | 90.1% |
| zebra | 98.1% | 93.5% | 95.7% |
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