SCIP: Scalable Cytometry Image Processing
Scalable Cytometry Image Processing (SCIP) is an open-source tool that implements an image processing pipeline on top of Dask, a distributed computing framework written in Python. SCIP performs normalization, image segmentation and masking, and feature extraction.
Check the docs for installation and usage instructions, and API documentation.
Development
Generating documentation
For publishing online:
cd docs
make clean
make html
For development with live reloading:
cd docs
make livehtml
Generate release changelog
git log v{previous version tag}..HEAD --oneline | xclip -sel clip
1 maintainer
Metadata
1 maintainer
Release files for scip 0.1.12
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| scip-0.1.12.tar.gz | 60.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scip-0.1.12-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 122.3 kB
Release files / scip-0.1.12.tar.gz
| Download URL | scip-0.1.12.tar.gz |
|---|---|
| Size | 60.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.10
|
Release files / scip-0.1.12-py3-none-any.whl
| Download URL | scip-0.1.12-py3-none-any.whl |
|---|---|
| Size | 62.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.10
|
