LACSS
LACSS is a deep-learning model for 2D/3D single-cell segmentation from microscopy images.
pip install lacss
Models checkpoints
Multi-modality (2D + 3D)
| name | #params | download | mAP LiveCell* | mAP Cellpose* | mAP NIPS* | ovule (3D)* | platynereis (3D)* |
|---|---|---|---|---|---|---|---|
| small | 60M | model | 56.3 | 52.0 | 54.2 | 44.4 | 56.7 |
| base | 152M | model | 57.1 | 56.0 | 62.9 | 47.0 | 60.8 |
| base-e | 304M | model | 57.4 | 58.3 | 65.7 | 49.8 | 61.9 |
- mAP is the average of APs at IOU threshoulds of 0.5-0.95 (10 segments). Evaluations are on either testing or validation split of the corresponding datasets.
For benchmarking (2D only)
| name | #params | training data | download | AP50 | AP75 | mAP |
|---|---|---|---|---|---|---|
| small-2dL | 40M | LiveCell | model | 84.3 | 61.1 | 57.4 |
| small-2dC | 40M | Cellpose+Cyto2 | model | 87.6 | 62.0 | 56.4 |
| small-2dN | 40M | NIPS challenge | model | 84.6 | 64.8 | 57.3 |
Deployment
You can deploy the models as an GRPC server using the biopb.image protocol:
python -m lacss.deploy.remote_server --modelpath=<model_file_path>
Public server
The Lacss public GRPC server is available here: lacss.biopb.org:443
The server is running the base model supporting both 2d and 3d segmentation.
For end user
- Trackmate-Lacss is the recommended GUI client for FIJI users. This plugin integrate with TrackMate for interactive cell segmentation and cell tracking.
- napari-biopb is recommended for napari users.
- For setting up your analysis pipeline programmatically, see this example notebook.
Why LACSS?
-
Multi-modality: works on both 2D (multichannel) images and 3D image stacks.
-
Speed: optimized for GPU due to the end-to-end design and the elimination of CPU-dependent post-processings.
-
Point-supervised training: Lacss is a multi-task model with a separate "localization" head (besides the segmentation head) predicting cell locations. This also means that you can train/fine-tune cell-segmentation using only point labels. See references for details.
Give It A Try:
Gradio Demo: try your own images (2D only)
Colabs
Inference
Train
Documentation
References
1 maintainer
Metadata
1 maintainer
Release files for lacss 0.15.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| lacss-0.15.2.tar.gz | 75.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| lacss-0.15.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 174.6 kB
Release files / lacss-0.15.2.tar.gz
| Download URL | lacss-0.15.2.tar.gz |
|---|---|
| Size | 75.1 kB |
| Tags | Source |
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Release files / lacss-0.15.2-py3-none-any.whl
| Download URL | lacss-0.15.2-py3-none-any.whl |
|---|---|
| Size | 99.5 kB |
| Tags | Python 3 |
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