Update README.md

README.md

@@ -7,31 +7,85 @@
 [![codecov](https://codecov.io/gh/aaristov/napari-segment/branch/main/graph/badge.svg)](https://codecov.io/gh/aaristov/napari-segment)
 [![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-segment)](https://napari-hub.org/plugins/napari-segment)
 
-Segment organoids and measure intensities
+Segment organoids in brightfield from nd2 stack
 
 ----------------------------------
 
 This [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.
 
-<!--
-Don't miss the full getting started guide to set up your new package:
-https://github.com/napari/cookiecutter-napari-plugin#getting-started
-
-and review the napari docs for plugin developers:
-https://napari.org/plugins/stable/index.html
--->
 
 ## Installation
 
-You can install `napari-segment` via [pip]:
-
-    pip install napari-segment
-
-
-
-To install latest development version :
-
-    pip install git+https://github.com/aaristov/napari-segment.git
+```pip install git+https://github.com/aaristov/napari-segment.git```
+
+## Usage for segmentation
+
+1. Drag your nd2 file into napari
+2. Lauch Plugins -> napari-segment: Segment prognoid
+3. Select the brightfield channel
+4. The data is lazily loaded from nd2 dataset and dynamically segmented in the viewer. 
+5. Theshold and erode parameters allow you to adjust segmentation -> they all will appear in the Detections layer
+6. Min/max diameter and eccentricity allow you to filter out unwanted regions -> the good regions will appear in the "selected labels" layer.
+7. You can deactivate the Detection layer with a checkbox.
+8. Once saticfied, simply save the selected labels layer with build-in napari saver for future use and downstream analysis.
+
+![image](https://user-images.githubusercontent.com/11408456/176637480-aec8f6f7-d1fe-44dc-b6cd-ccea675c0dc9.png)
+
+## Usage for multicale zarr preview
+1. Drag and drop the folder with mutiscale zarr dataset.
+2. The plugin will look for the napari attributes in the .zattr file and render the stack accordingly. See the example below for 4D dataset:
+```json
+{
+    "multiscales": {
+        "multiscales": [
+            {
+                "channel_axis": 1,
+                "colormap": [
+                    "gray",
+                    "green",
+                    "blue"
+                ],
+                "datasets": [
+                    {
+                        "path": "0"
+                    },
+                    {
+                        "path": "1"
+                    },
+                    {
+                        "path": "2"
+                    },
+                    {
+                        "path": "3"
+                    }
+                ],
+                "lut": [
+                    [
+                        1000,
+                        30000
+                    ],
+                    [
+                        440,
+                        600
+                    ],
+                    [
+                        0,
+                        501
+                    ]
+                ],
+                "name": [
+                    "BF",
+                    "TRITC",
+                    "mask"
+                ],
+                "title": "BF_TRITC_aligned.zarr",
+                "type": "nd2",
+                "version": "0.1"
+            }
+        ]
+    }
+}
+```
 
 
 ## Contributing