onnx biology en zh la license:mit region:us
---
license: mit
language:
- en
- zh
- la
metrics:
- accuracy
tags:
- biology
---

This study introduces a target detection model specifically designed for insect recognition, distinguished by its support for 2037 different categories of insects, covering various classification levels such as order, family, genus, or species. The model aims to address the extensive and challenging issues in the field of biological recognition, efficiently handling the diversity and complexity of insects and other arthropods. Its primary objective is to achieve accurate detection of a large-scale dataset of insect images, ensuring precise classification and target detection for each category. This research provides an advanced technological tool for fields such as ecology, agricultural protection, and biodiversity research. The innovation lies in the model's extensive category support, enabling outstanding performance in real-world scenarios involving unknown insects or other arthropods.

## Maintenance
```bash
GIT_LFS_SKIP_SMUDGE=1 git clone git@hf.co:MuGeminorum/insecta
```

## Mirror
<https://www.modelscope.cn/models/MuGeminorum/insecta>

## Reference
[1] <https://github.com/quarrying/quarrying-insect-id>