README.md

metadata

title: DynaCell Virtual Staining Demo
emoji: 🔬
colorFrom: gray
colorTo: gray
sdk: gradio
sdk_version: 5.29.0
app_file: app.py
pinned: false
python_version: '3.12'
suggested_hardware: zero-a10g
models:
  - biohub/dynacell-checkpoints
datasets:
  - biohub/dynacell-demo-data

DynaCell Virtual Staining Demo

Predict fluorescence channels (membrane, nuclei, or organelle structure) from phase-contrast OME-Zarr using three models:

• CELL-Diff — flow-matching diffusion model
• FNet3D — 3-D U-Net (FNet architecture)
• VSCyto3D — masked-autoencoder pretrained U-Net

Quick start

1. Select an organelle from the dropdown.
2. Click Load Demo Data to fetch the matching A549-cell demo dataset directly into the Space — no download/upload needed.
3. Run predictions in Tab 1 or generate the CELL-Diff ODE trajectory in Tab 2.

Using your own data

The input must be an OME-Zarr HCS store zipped into a single .zip file, with layout:

your_data.zarr/
  0/0/fov0000/0      # array shape (T, C, Z, Y, X)
                     # C[0] = Phase3D, Z = 16, YX = 512×512

Use iohub to create compatible zarr stores.