Cellsam Onnx
modified-apache-2.0
Model source
- Kind
- Other
- File size
- 569 KB–4.38 MB
- Version
- vRevision 98c9f0f
- Updated
- Sep 27, 2026
- Downloads
- 0
- Tasks
- Image segmentation
- Source
- Hugging Face
Source description
CellSAM (ONNX)
This repository contains the ONNX export of the CellSAM model for cell segmentation.
⚠️ LICENSE WARNING: NON-COMMERCIAL / ACADEMIC USE ONLY ⚠️
This model is derived from the original CellSAM work and is subject to a Modified Apache License 2.0.
Grant of Copyright License: ... each Contributor hereby grants to You a non-commercial, academic perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license...
See the LICENSE file for full terms. Commercial use requires contacting the original authors (vanvalenlab@gmail.com).
Usage with cellsam-rs
This model is designed for high-performance inference using cellsam-rs.
# Install cellsam-rs (example)
cargo install cellsam-rs
# Run inference
cellsam-rs infer \
--input image.tif \
--model models/cellsam-onnx \
--output mask.tif
Model Details
- Original Repository: vanvalenlab/cellSAM
- Architecture: SAM-based (Segment Anything Model) specialized for cell segmentation.
- Input: Phase contrast + Fluorescence images (2-channel).
- Format: ONNX (Opset 17).
Citation
If you use this model, please cite the original CellSAM paper:
@article{Israel2024,
title={CellSAM: A Foundation Model for Cell Segmentation},
author={Israel, Uri and others},
journal={Nature Methods},
year={2024}
}
Sources
1 source
Sources
1 sourceVerified Sep 27
Model artifacts
3 artifacts
Model artifacts
3 artifactsSource excerpts
2 excerpts
Source excerpts
2 excerpts--- license: other license_name: modified-apache-2.0 license_link: LICENSE pipeline_tag: image-segmentation tags: - biology - microscopy - segmentation - cell-segmentation - onnx --- # CellSAM (ONNX) This repository contains the **ONNX export** of the [CellSAM](https://github.com/vanvalenlab/cellSAM) model for cell segmentation. **⚠️ LICENSE WARNING: NON-COMMERCIAL / ACADEMIC USE ONLY ⚠️** This model is derived from the original [CellSAM](https://github.com/vanvalenlab/cellSAM) work and is subject to a **Modified Apache License 2.0**. > **Grant of Copyright License:** ... each Contributor hereby grants to You a **non-commercial, academic** perpetual, worldwide, non-exclusive, no-charge, royalty-free, irrevocable copyright license... See the [LICENSE](LICENSE) file for full terms. Commercial use requires contacting the original authors (`vanvalenlab@gmail.com`). ## Usage with cellsam-rs This model is designed for high-performance inference using [cellsam-rs](https://github.com/keejkrej/cellsam-rs). ```bash # Install cellsam-rs (example) cargo install cellsam-rs # Run inference cellsam-rs infer \ --input image.tif \ --model models/cellsam-onnx \ --output mask.tif ``` ## Model Details - **Original Repository:** [vanvalenlab/cellSAM](https://github.com/vanvalenlab/cellSAM) - **Architecture:** SAM-based (Segment Anything Model) specialized for cell segmentation. - **Input:** Phase contrast + Fluorescence images (2-channel). - **Format:** ONNX (Opset 17). ## Citation If you use this model, please cite the original CellSAM paper: ```bibtex @article{Israel2024, title={CellSAM: A Foundation Model for Cell Segmentation}, author={Israel, Uri and others}, journal={Nature Methods}, year={2024} } ```
Source context: 0 downloads · 0 likes · Pipeline image-segmentation · Repo keejkrej/cellsam-onnx
