GUI tool for labeling micronuclei images
Project description
micronuclAI labeling tool
Installation
On your preferred python environment, run the following command:
pip install micronuclAI-labeling
Usage
To launch micronuclAI labeling tool, run the following command:
python -m micronuclai_labeling --input path/to/image --mask path/to/mask --out path/to/outfile.csv
Once the tool is launched, you can use the following keyboard shortcuts:
The tool works by pressing any of the keys from 0-9:
The key 0 for no micro-nuclei present.
The keys 1-9 for the number of observed micro-nuclei in the image.
The key r is used to go back one image (in case any labeling mistake occurs).
NOTE: Labeling doesn't have to be done in one session, it can be resumed later on.
NOTE: Once labeling is complete the tool will not initiate.
NOTE: Output, Input and Mask paths are required and must be the same in order to resume labeling.
License
micronuclAI labeling tool offers a dual licensing mode the GNU Affero General Public License v3.0 - see LICENSE and ESSENTIAL_LICENSE_CONDITIONS.txt
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file micronuclai_labeling-0.1.1.tar.gz
.
File metadata
- Download URL: micronuclai_labeling-0.1.1.tar.gz
- Upload date:
- Size: 16.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.9.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c28f56a47a84228eb606899a8587dc69dc2c2f5553a78bcdf53cd10bde6b1a95 |
|
MD5 | 69844d530148c0a447cf5a02b4481dbb |
|
BLAKE2b-256 | 224f860aa587f5fff306da8d54534f93a08b7ee11c0a336c78d30a7e28d97f2a |
File details
Details for the file micronuclAI_labeling-0.1.1-py3-none-any.whl
.
File metadata
- Download URL: micronuclAI_labeling-0.1.1-py3-none-any.whl
- Upload date:
- Size: 16.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.0 CPython/3.9.19
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 71c66447cdf90df359cfd9271361f1964d545cef21b0e40dc7c04e5833548829 |
|
MD5 | ace7b51c71f2c0c4f959b2117b74f2f3 |
|
BLAKE2b-256 | 29a32117649adcdeb7ae50773797b1cf04511c83747d2e79851fe1152b0fe7b3 |