Merge pull request #8 from haesleinhuepf/zoom

Zoom, Insight, Documentation
haesleinhuepf · Dec 23, 2022 · 3db7292 · 3db7292
2 parents 7e0b0df + 96ca544
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diff --git a/README.md b/README.md
@@ -1,4 +1,4 @@
-# stackview
+# stackview 🧊👀
 Interactive image stack viewing in jupyter notebooks based on 
 [ipycanvas](https://ipycanvas.readthedocs.io/) and 
 [ipywidgets](https://ipywidgets.readthedocs.io/en/latest/). 
@@ -28,31 +28,62 @@ If you run the installation from within a notebook, you need to restart Jupyter
 You can use `stackview` from within jupyter notebooks as shown below.
 Also check out the demo in [![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/haesleinhuepf/stackview/HEAD?filepath=docs%2Fdemo.ipynb)
 
+There are also example notebooks in [this folder](https://github.com/haesleinhuepf/stackview/tree/main/docs).
+
 Starting point is a 3D image dataset provided as numpy array. 
 ```python
 from skimage.io import imread
 image = imread('data/Haase_MRT_tfl3d1.tif', plugin='tifffile')
 ```
 
+### Slice view
+
 You can then view it slice-by-slice:
 ```python
 import stackview
 stackview.slice(image, continuous_update=True)
 ```
 ![](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/demo_slice.gif)
 
+### Static insight views
+
+The `insight` function turns a numpy-array into a numpy-compatible array that has an image-display in jupyter notebooks.
+
+```python
+insight(image[60])
+```
+
+![img.png](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/insight_demo.png)
+
+Images of 32-bit and 64-bit type integer are displayed as labels. 
+
+```python
+blobs = imread('data/blobs.tif')
+labels = label(blobs > 120)
+
+insight(labels)
+```
+
+![img.png](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/labels_demo.png)
+
+### Pick intensities
+
 To read the intensity of pixels where the mouse is moving, use the picker.
 ```python
 stackview.picker(image, continuous_update=True)
 ```
 ![](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/demo_picker.gif)
 
+### Orthogonal view
+
 Orthogonal views are also available:
 ```python
 stackview.orthogonal(image, continuous_update=True)
 ```
 ![](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/demo_orthogonal.gif)
 
+### Curtain
+
 Furthermore, to visualize an original image in combination with a processed version, a curtain view may be helpful:
 ```python
 stackview.curtain(image, modified_image * 65537, continuous_update=True)
@@ -77,13 +108,17 @@ stackview.curtain(slice_image, labels, continuous_update=True)
 
 ![](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/demo_curtain3.gif)
 
+### Side-by-side view
+
 A side-by-side view for colocalization visualization is also available.
 If you're working with time-lapse data, you can also use this view for visualizing differences between timepoints:
 ```python
 stackview.side_by_side(image_stack[1:], image_stack[:-1], continuous_update=True, display_width=300)
 ```
 ![](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/demo_side_by_side.gif)
 
+### Interact
+
 Exploration of the parameter space of image processing functions is available using `interact`:
 ```python
 from skimage.filters.rank import maximum
@@ -120,6 +155,18 @@ stackview.interact(gaussian, context=globals(), continuous_update=True)
 
 ![](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/demo_interact4.gif)
 
+To add an `insight`-view automatically to results of functions, you can add this.
+
+```python
+@jupyter_displayable_output
+def my_gaussian(image, sigma):
+    return gaussian(image, sigma)
+
+my_gaussian(image[60], 2)
+```
+
+![img.png](https://raw.githubusercontent.com/haesleinhuepf/stackview/main/docs/images/jupyter_displayable_output.png)
+
 ## Contributing
 
 Contributions, bug-reports and ideas for further development are very welcome.
@@ -135,6 +182,7 @@ If you encounter any problems, please create a thread on [image.sc] along with a
 
 ## See also
 There are other libraries doing similar stuff
+* [ipyannotations](https://github.com/janfreyberg/ipyannotations)
 * [napari](https://github.com/napari/napari)
 * [JNI's Volume Viewer based on Matplotlib](https://github.com/jni/mpl-volume-viewer)
 * [Holoviz hvPlot](https://hvplot.holoviz.org/user_guide/Gridded_Data.html#n-d-plots)

diff --git a/docs/demo.ipynb b/docs/demo.ipynb
diff --git a/docs/images/insight_demo.png b/docs/images/insight_demo.png
diff --git a/docs/images/jupyter_displayable_output.png b/docs/images/jupyter_displayable_output.png
diff --git a/docs/images/labels_demo.png b/docs/images/labels_demo.png
diff --git a/docs/insight.ipynb b/docs/insight.ipynb
diff --git a/docs/zoom.ipynb b/docs/zoom.ipynb
diff --git a/setup.py b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="stackview",
-    version="0.3.7",
+    version="0.3.8",
     author="Robert Haase",
     author_email="[email protected]",
     description="Interactive image stack viewing in jupyter notebooks",