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---
license: apache-2.0
---
# InsectSAM: Insect Segmentation and Monitoring
## Overview
InsectSAM is a fine-tuned version of Meta AI's `segment-anything` model, optimized for insect segmentation and monitoring in the Netherlands. Designed for use with the [DIOPSIS](https://diopsis.eu) camera systems, algorithms and datasets, it enhances the accuracy of insect biodiversity segmentation from complex backgrounds.
## Purpose
Trained to segment insects against diverse backgrounds, InsectSAM adapts to changing environments, ensuring its long-term utility for the DIOPSIS datasets.
## Model Architecture
Built on the `segment-anything` architecture, InsectSAM is fine-tuned on an insect-specific dataset and integrated with GroundingDINO for improved detail recognition.
## Quick Start
### Prerequisites
- Python
- Hugging Face Transformers
- PyTorch
### Usage
#### Install
```bash
!pip install --upgrade -q git+https://github.com/huggingface/transformers
!pip install torch
```
#### Load model via 🤗 Transformers
```python
from transformers import AutoProcessor, AutoModelForMaskGeneration
processor = AutoProcessor.from_pretrained("martintmv/InsectSAM")
model = AutoModelForMaskGeneration.from_pretrained("martintmv/InsectSAM")
```
### Notebooks
Explore InsectSAM's capabilities and integration with GroundingDINO through three Jupyter notebooks available on the RB-IBDM GitHub page:
- [**InsectSAM.ipynb**](https://github.com/martintmv-git/RB-IBDM/blob/main/InsectSAM/InsectSAM.ipynb): Training process
- [**InsectSAM_GroundingDINO.ipynb**](https://github.com/martintmv-git/RB-IBDM/blob/main/InsectSAM/InsectSAM_GroundingDINO.ipynb): Enhanced segmentation performance with GroundingDINO
- [**InsectSAM_script.ipynb**](https://github.com/martintmv-git/RB-IBDM/tree/main/Image%20Processing%20Scripts/InsectSAM): Image processing script
GitHub: https://github.com/martintmv-git/RB-IBDM/tree/main/InsectSAM |