Rootscope / README.md
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RootScope v4: manuscript model (LightGBM per round, 3 seeds, layer + soft-neighbor context, radial prior)
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---
title: 'RootScope: Cross-species Root Cell-Type Classification from Confocal Microscopy Images'
emoji: 🌱
colorFrom: green
colorTo: blue
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: mit
short_description: Classify root cell types across species from confocal TIFFs
---
# RootScope web app
Web front end for [RootScope](https://github.com/ct-tranchau/Rootscope).
Upload a confocal root cross-section TIFF and get back a labeled overlay and a
per-cell CSV. Every cell is segmented with Cellpose-SAM and assigned to one of
nine cell types: root cap, epidermis, exodermis, cortex, endodermis,
pericycle, stele, xylem, phloem.
## How to use
1. Upload a raw confocal TIFF (not a mask). Pixel size is read from the OME
metadata.
2. Optionally type the species name. It is not required; if given, it is
checked against the species table shipped with the package.
3. Press Run. Segmentation and the DINOv2 embeddings run on the GPU; a
700x700 image with about 200 cells takes about 20 to 45 seconds.
4. Download the overlay image and the CSV of per-cell predictions.
One image at a time. For batches use the command line: `rootscope --tif-dir`.
## Run it locally
```bash
conda activate rootscope
pip install gradio
python webapp/app.py
```
Model weights download from [ct-tranchau/Rootscope](https://huggingface.co/ct-tranchau/Rootscope)
on first use.
## Author
Tran Chau (tnchau@vt.edu)