napari | napari : a fast , interactive , multi-dimensional image | Data Visualization library
kandi X-RAY | napari Summary
kandi X-RAY | napari Summary
napari: a fast, interactive, multi-dimensional image viewer for python
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Top functions reviewed by kandi - BETA
- Visualize an image
- Create a viewer based on add_method
- Return a QApplication instance
- Get napari settings
- Removes the specified value from the set
- Called when the cache has changed
- Compute a precisedelta
- Translate message
- Return the translation for the current locale
- Initialize from kwargs
- Return a dictionary of source config file settings
- Return a list of all the ideal chunks that can draw the given set
- Setup UI
- Move plan to dest
- Set view slice
- Handles click along a plane
- Setup the UI
- Return a list of LinkKey objects linked to the given layers
- Select the layer
- Opens a grid popup
- Set keybinding
- Blend HSV to RGB
- Validates that a collection of objects is a sequence of length n
- Return the package metadata
- Creates a source of nested env_settings
- Shade an RGB color using a cmap
napari Key Features
napari Examples and Code Snippets
Lines of Code : 31License : Permissive (BSD-3-Clause)
Copyimport dask.array as da
import zarr
from napari_lazy_openslide import OpenSlideStore
store = OpenSlideStore('tumor_004.tif')
grp = zarr.open(store, mode="r")
# The OpenSlideStore implements the multiscales extension
# https://forum.image.sc/t/mult from napari_animation import Animation
animation = Animation(viewer)
viewer.dims.ndisplay = 3
viewer.camera.angles = (0.0, 0.0, 90.0)
animation.capture_keyframe()
viewer.camera.zoom = 2.4
animation.capture_keyframe()
viewer.camera.angles = (-7.0, 1 from napari_animation import Animation
animation = Animation(viewer)
viewer.dims.ndisplay = 3
viewer.camera.angles = (0.0, 0.0, 90.0)
animation.capture_keyframe()
viewer.camera.zoom = 2.4
animation.capture_keyframe()
viewer.camera.angles = (-7.0, 1 Py_BEGIN_ALLOW_THREADS
// computation goes here
Py_END_ALLOW_THREADS
viewer.add_points(
blobs[:, :-1], size=blobs[:, -1], name='points', scale=spacing
)
from skimage.util import label_points
labels = label_points(blobs[:, :-1], bblobs.shape)
viewer.add_labels(labels, scale=spacfrom scipy import ndimage
vol = np.zeros((512, 512, 512), dtype=states_int.dtype)
# add data to vol
vol[tuple(np.split(states_int, vol.ndim, axis=1))] = values[:, np.newaxis]
# apply gaussian filter, sigma=5 in this case
vol = ndimage.gauimport numpy as np
import napari
from skimage import data, filters # Just to generate some test data (3D blobs).
with napari.gui_qt():
# Generate some test data (smooth 3D blob shapes)
imgarray = filters.gaussian(np.squeeze(np.sCommunity Discussions
Trending Discussions on napari
QUESTION
I am working on a scientific algorithm (image processing), which is written in C++, and uses lots of parallelization, handled by OpenMP. I need it to be callable from Python, so I created a CPython package, which handles the wrapping of the algorithm.
Now I need some UI, as user interaction is essential for initializing some stuff. My problem is that the UI freezes when I run the algorithm. I start the algorithm in a separate thread, so this shouldn't be a problem (I even proved it by replacing the function call with time.sleep, and it works fine, not causing any freeze). For testing I reduced the UI to two buttons: one for starting the algorithm, and another just to print some random string to console (to check UI interactions).
I also experienced something really weird. If I started moving the mouse, then pressed the button to start the computation, and after that kept moving the mouse continuously, the UI did not freeze, so hovering over the buttons gave them the usual blueish Windows-style tint. But if I stopped moving my mouse for a several seconds over the application window, clicked a button, or swapped to another window, the UI froze again. It's even more strange that the UI stayed active if I rested my mouse outside of the application window.
Here's my code (unfortunately I cannot share the algorithm for several reasons, but I hope I manage to get some help even like this):
ANSWER
Answered 2022-Mar-22 at 15:43Because of Python's "Global Interpreter Lock", only one thread can run Python code at a time. However, other threads can do I/O at the same time.
If you want to allow other threads to run (just like I/O does) you can surround your code with these macros:
QUESTION
I'm trying to use blob log or blog dog for blob detection in a 3D image using skimage. I'm using napari and binary blob (3D) images as a sample (but this will not be the image I will be using later this just has clear-cut blobs). However, I'm having trouble applying the blobs to the image/adding it to the viewer.
Skimage has a 2D image example using matplotlib adding circles to the image, but I would like to use this to identify blobs on the 3D image and create either a binary image (a mask essentially) or labels.
This is what I have, but I'm not sure where to go from here:
...ANSWER
Answered 2021-Nov-04 at 03:47What are you trying to do after? Do you need the blob sizes or only the positions? The answer depends a lot on the question. Here's three answers:
- Just visualise the blobs as points:
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