Deep Learning toolbox for WSI (digital histopatology) analysis
- Responsive WSI image viewer
- State of the art cancer AI pipeline to segment the and display the cancer cell
Running of the AI pipeline requires a GPU and several deep learning modules. However, you can run just the UI as well.
Just the UI
The following command will install only the dependencies listed above.
pip install DigiPathAI
Entire AI pipeline
The following command will install the dependencies mentioned
pip install "DigiPathAI[gpu]"
Both installation methods install the same package, just different dependencies. Even if you had installed using the earlier command, you can install the rest of the dependencies manually.
Traverse to the directory containing the openslide images and run the following command.
digipathai <host: localhost (default)> <port: 8080 (default)>
Python API usage
The application also has an API which can be used within python to perform the segmentation.
from DigiPathAI.Segmentation import getSegmentation prediction = getSegmentation(img_path, patch_size = 256, stride_size = 128, batch_size = 32, quick = True, tta_list = None, crf = False, save_path = None, status = None)
Release history Release notifications
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size DigiPathAI-0.1.3-py3.5.egg (2.6 MB)||File type Egg||Python version 3.5||Upload date||Hashes View hashes|