Spaces:
Sleeping
Sleeping
| title: Cellpose + SAM DRG Segmentation | |
| license: mit | |
| sdk: streamlit | |
| emoji: 🏃 | |
| colorFrom: indigo | |
| colorTo: purple | |
| app_file: streamlit_app.py | |
| # Spinal Cord Segmentation Pipeline | |
| Automated, end‑to‑end processing and segmentation of spinal‑cord microscopy images with [Cellpose](https://cellpose.readthedocs.io/). | |
| ## Overview | |
| This repository provides a **turn‑key workflow** for turning raw histological slides of the spinal cord (TIFF) into high‑quality, full‑resolution segmentation masks—in a *single command*. | |
| ## Key Features | |
| | Stage | Purpose | | |
| |-------|---------| | |
| | **TIFF → PNG conversion** | Converts raw `.tiff` slides to compressed `.png`, with optional down‑scaling to speed up processing. | | |
| | **Smart tiling** | Splits very large images into manageable tiles that fit comfortably in GPU/CPU memory. | | |
| | **Cellpose inference** | Runs the *cyto3* (default) or any other Cellpose model on every tile. | | |
| | **Mask stitching** | Re‑assembles the individual tile masks into a single, full‑resolution segmentation mask. | | |
| ## Requirements | |
| * Python **3.9+** | |
| * GPU‑enabled PyTorch build (optional but recommended) | |
| * Dependencies (installed automatically via `requirements.txt`): | |
| * `cellpose==3.1.1.1` | |
| * `opencv‑python` | |
| * `numpy` | |
| * `pillow` | |
| * `tifffile` | |
| ## Installation | |
| ```bash | |
| # Clone the repository | |
| git clone https://github.com/your‑username/spinal‑cord‑segmentation.git | |
| cd spinal‑cord‑segmentation | |
| # Create / activate a virtualenv (optional but recommended) | |
| python -m venv .venv | |
| source .venv/bin/activate # Windows: .venv\Scripts\activate | |
| # Install Python dependencies | |
| pip install -r requirements.txt | |
| ``` | |
| ## Quick Start | |
| 1. **Place** your raw `.tiff` images in `data/input/` (or adjust the paths in `bin/constants.py`). | |
| 2. **Run** the pipeline: | |
| ```bash | |
| python main.py | |
| ``` | |
| 3. **Collect** your results: | |
| * PNG conversions → `data/png/` | |
| * Split tiles → `data/tiles/` | |
| * Cellpose masks → `data/masks/` | |
| * Stitched masks → `data/output/` | |
| ## Detailed Workflow | |
| ```mermaid | |
| flowchart LR | |
| A[TIFF images] --> B[generate_pngs.py]:::step | |
| classDef step fill:#fafafa,stroke:#333,stroke-width:1px; | |
| B --> C[generate_split_images.py]:::step | |
| C --> D[run_cellpose.py]:::step | |
| D --> E[generate_masks.py]:::step | |
| E --> F[Final segmentation]:::step | |
| ``` | |
| *All paths, tile overlap, and Cellpose parameters are configurable in* **`bin/constants.py`**. | |
| ## Project Layout | |
| ``` | |
| . | |
| ├── main.py # Orchestrates the full pipeline | |
| ├── bin/ | |
| │ ├── constants.py # Centralised paths & tunables | |
| │ ├── generate_pngs.py # TIFF → PNG converter | |
| │ ├── generate_split_images.py | |
| │ └── generate_masks.py | |
| ├── model/ | |
| │ └── run_cellpose.py # Wrapper around Cellpose API | |
| ├── requirements.txt | |
| └── LICENSE | |
| ``` | |
| ## License | |
| Distributed under the terms of the **MIT License**. See `LICENSE` for full text. | |
| ## Contributing | |
| Contributions, issues and feature requests are welcome! Please open an issue or submit a pull request — and ensure your code passes `flake8`/`black` checks and includes appropriate tests. | |
| ## Citation | |
| If you use this pipeline in your research, please cite *Cellpose* **and** this repository: | |
| ```text | |
| @article{stringer_cellpose_2021, | |
| title = {Cellpose: a generalist algorithm for cellular segmentation}, | |
| author = {Stringer, Carsen and Pachitariu, Marius}, | |
| journal = {Nature Methods}, | |
| year = {2021} | |
| } | |
| ``` |