Tools to visualize HCS data stored in zarr files. The tools work locally or can be run in a remote server.
The dask package is used to retrieve the HCS data from zarr files. This allows to visualize large scale images without the need to fully load them in memory.
Napari is a multi-dimensional viewer that displays numpy arrays as images. This package can be easily extended to integrate more functionalities.
python ./src/napari_viewer.py -z HCS_image.zarr
To run the viewer from a server, build and shell into the container defined by hcs_zarr_viewers.def. The server must allow X11 forwarding to open the viewer.
Neuroglancer is a web-based volumetric data viewer. It can be used to visualize three-dimensional data. The limitation of working with zarr files is that neuroglancer requires more coding to work with the pyramid representation that zarr offers.
To use the viewer based on neuroglancer, run it in interactive mode. Otherwise, the web environment will be closed before it can be used. At running the viewer, it will print an url path that can be pasted in the browser.
python -i ./src/neuroglancer_viewer.py -z HCS_image.zarr
To run the neuroglancer viewer from a server, build and shell into the container defined by hcs_zarr_viewers.def. Before running the code, export the environment variable HOSTNAME_IP to point to the server’s IP.
export HOSTNAME_IP=$(hostname -i)
Vizarr is a minimal viewer to display zarr inside jupyter notebooks. To use vizarr, it is needed to install de ImJoy Jupyter extension.
The imjoy_viewer.ipynb notebook provides an example of HCS data visualization in Jupyter.
For now, vizarr cannot be used in a jupyter notebook hosted in a remote server. To do so, it would be necessary to modify the container definition to allow the ImJoy Jupyter extension installation.
The example codes provded in this repository work with images stored in zarr files. For now, the groups selecetion is hardcoded, so only the group '0' is accessible. This could be improved by inspecting the structure of the zarr file and identifying the groups structure.