Add README.md (#12)

README.md

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+# vizarr
+
+![Multiscale OME-Zarr in Jupyter Notebook with Vizarr](/screenshot.png)
+
+Vizarr is a minimal, purely client-side program for viewing Zarr-based images. It is built with 
+[Viv](https://hms-dbmi.github.com/viv) and exposes a Python API using the 
+[`imjoy-rpc`](https://github.com/imjoy-team/imjoy-rpc), allowing users to programatically view multiplex 
+and multiscale images from within a Jupyter Notebook. The ImJoy plugin registers a codec for Python 
+`zarr.Array` and `zarr.Group` objects, enabling Viv to securely request chunks lazily via 
+[Zarr.js](https://github.com/gzuidhof/zarr.js/). This means that other valid zarr-python 
+[stores](https://zarr.readthedocs.io/en/stable/api/storage.html) can be viewed remotely with Viv, 
+enabling flexible workflows when working with large datasets.
+
+### Remote image registration workflow
+We created Vizarr to enhance interactive multimodal image alignment using the 
+[wsireg](https://github.com/NHPatterson/wsireg) library. We describe a rapid workflow were 
+comparison of registration methods as well as visual verification of alignnment can be assessed 
+remotely, leveraging computational resources on remote servers for rapid image processing and 
+Viv for interactive web-based visualization. For more information, please read our pre-print.
+
+### Data types
+Vizarr supports viewing 2D slices of n-Dimensional Zarr arrays, allowing users to choose 
+a single channel or blended composites of multiple channels during analysis. It has special support 
+for the developing [OME-Zarr format](https://github.com/ome/omero-ms-zarr/blob/master/spec.md)
+for multiscale and multimodal images. Currently [Viv](https://hms-dbmi.github.com/viv) supports 
+`u1`, `u2`, `u4`, and `f4` arrays, but contributions are welcome to support more `np.dtypes`!
+
+### Getting started 
+The easiest way to get started with `vizarr` is to open the example [Jupyter Notebook](example/README.md).
+
+### Limitations
+`vizarr` was built to support the registration use case above where multiple, pyramidal OME-Zarr images
+are viewed within a Jupyter Notebook. Support for other Zarr arrays is supported but not as well tested. 
+More information regarding thew viewing of generic Zarr arrays can be found in in the example notebooks.
+

example/README.md

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 ### Getting started 
 
-This example will work in the jupyter notebook (not jupyterlab), and requires the `imjoy-rpc` plugin.
-
-```bash
-$ pip install imjoy-rpc
-```
-
-```bash
-$ python create_fixture.py # creates ome-zarr test
-```
+This example will work in the jupyter notebook (not jupyterlab), and requires the `imjoy-jupyter-extension`.
 
 ```bash
+$ pip install -U imjoy-jupyter-extension
+$ pip install -r requirements.txt
 $ jupyter notebook imjoy_example.ipynb
 ```
+

example/requirements.txt

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+numpy
+ipywidgets>=7.0.0
+scikit-image
+imjoy>=0.10.0
+fsspec
+imjoy-rpc
+zarr