Image dataset for training of an insect classification model

This version is deprecated! Please use the updated Insect Detect - insect classification dataset v2 with more images and classes.

This dataset contains images of various insects and some other arthropods, sitting on or flying above an artificial flower platform. All images were automatically recorded with the Insect Detect DIY camera trap, a hardware combination of the Luxonis OAK-1, Raspberry Pi Zero 2 W and PiJuice Zero pHAT for automated insect monitoring (bioRxiv preprint).
This classification dataset contains the cropped bounding boxes, exported from the Insect_Detect_detection dataset together with 290 new images of Episyrphus balteatus.
Classes
The following classes were annotated in this dataset:

wasp (mostly Vespula sp.)
hbee (Apis mellifera)
fly (mostly Brachycera)
hovfly (various Syrphidae, e.g. Eupeodes corollae, Scaeva pyrastri)
episyr_balt (Episyrphus balteatus)
other (all Arthropods with insufficient occurences, e.g. various Hymenoptera, true bugs, beetles)
shadow (shadows of the recorded insects)
View the Health Check for more info on class balance.
Deployment
You can use this dataset as starting point to train your own insect classification models. Check the model training instructions for more information.
To deploy the image classification model (ONNX format) on your PC for fast CPU inference, follow the provided Step by Step instructions. Open source Python scripts to deploy the trained model can be found at the insect-detect-ml GitHub repo.