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