Insectsam

🚀 InsectSAM: Insect Segmentation and Monitoring

InsectSAM is a specialized model fine - tuned from Meta AI's segment - anything for accurate insect segmentation and monitoring in the Netherlands, especially for use with DIOPSIS camera systems, algorithms, and datasets.

🚀 Quick Start

Prerequisites

• Python
• Hugging Face Transformers
• PyTorch

Usage

Install

!pip install --upgrade -q git+https://github.com/huggingface/transformers
!pip install torch

Load model via 🤗 Transformers

from transformers import AutoProcessor, AutoModelForMaskGeneration

processor = AutoProcessor.from_pretrained("martintomov/InsectSAM")
model = AutoModelForMaskGeneration.from_pretrained("martintomov/InsectSAM")

Notebooks

Explore InsectSAM's capabilities and integration with GroundingDINO through three Jupyter notebooks available on the RB - IBDM GitHub page:

• InsectSAM.ipynb: Training process
• InsectSAM_GroundingDINO.ipynb: Enhanced segmentation performance with GroundingDINO
• InsectSAM_script.ipynb: Image processing script

GitHub: https://github.com/martintmv-git/RB-IBDM/tree/main/InsectSAM

✨ Features

• 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 camera systems, algorithms and datasets, it enhances the accuracy of insect biodiversity segmentation from complex backgrounds.
• Trained to segment insects against diverse backgrounds, it adapts to changing environments, ensuring its long - term utility for the DIOPSIS datasets.

🔧 Technical Details

• Built on the segment - anything architecture, InsectSAM is fine - tuned on an insect - specific dataset and integrated with GroundingDINO for improved detail recognition.

📄 License

This project is licensed under the Apache 2.0 license.