Comments (5)
Also there doesnt seem to be any functional docs for using the repo on 2d images
from connected-components-3d.
Hi Ademord,
Thanks for writing! I'm glad you are finding this library potentially useful.
Also there doesnt seem to be any functional docs for using the repo on 2d images
You can use 2D images just like 3D except that if you want to specify the 2D connectivity, you'll get better performance if you write connectivity=4
or connectivity=8
than with 6, 18, or 26 which are effectively 4, 8, and 8 when applied to 2D.
Currently what I have is a depth image, with a separated rgb.
cc3d only handles single channel images. To process it with cc3d, you'll need to convert the depth image from a 3-channel uint8 image (presumably) to a (u)int32 image with a single depth number per pixel.
Is there a way for me to visualize the results from code you have on your main README?
You can visualize the array in many different ways, but here is one:
pip install cloud-volume
import cc3d
from cloudvolume import view
out_labels = cc3d.connected_components(labels)
view(out_labels, segmentation=True)
That will generate a link to localhost:8080 and you can view the 3D volume by scrolling through it and reslicing different axes.
Will
from connected-components-3d.
@william-silversmith how can we save the image obtained after applying cc3d?
from connected-components-3d.
You can also do:
from cloudvolume.lib import save_images
out_labels = cc3d.connected_components(labels)
save_images(out_labels)
from connected-components-3d.
Closing this issue due to lack of activity. Let me know if you still need help!
from connected-components-3d.
Related Issues (20)
- Applying Dust and largest_k dtype output option HOT 2
- dust sugnature HOT 1
- Massive memory Leak HOT 7
- 1D Array of 4 Elements Incorrect HOT 5
- Cannot find reference 'dust' in 'cc3d.py' HOT 2
- Question on comparing individual lesions between two masks based on the cc3d.statistics output. HOT 1
- Additional metrics support HOT 2
- Does cc3d also work with memmory-mapped numpy arrays and array-like data? HOT 14
- cc3d.statistics["bounding_boxes"] are wrong HOT 1
- largest_k fails for transposed arrays HOT 6
- About the lastest_k function HOT 4
- Statistics output HOT 7
- Question on the output of contacts HOT 9
- Periodic Boundary Conditions HOT 4
- Is the output label of largest_k ordered? HOT 2
- Add a better error for type support. HOT 4
- Any way to make this GPU Compatible? HOT 6
- Applying dust to labels does not do anything HOT 3
- Support for Numpy 2.0 HOT 3
- cc3d.dust fails HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from connected-components-3d.