lungs_segmentation
Automated lung segmentation in chest-x ray
Train pipeline: https://github.com/alimbekovKZ/lungs_segmentation_train
Installation
pip install lungs-segmentation
Example inference
Jupyter notebook with the example:
WebApp
https://lungssegmentation.herokuapp.com/
Models weights
| model | best dice | Mb |
|---|---|---|
| resnet34 | 0.9657 | 103.4 |
| densenet121 | 0.9655 | 62.8 |
Usage
Code example for resnet34:
from lungs_segmentation.pre_trained_models import create_model
import lungs_segmentation.inference as inference
model = create_model("resnet34")
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
model = model.to(device)
plt.figure(figsize=(20,40))
plt.subplot(1,1,1)
image, mask = inference.inference(model,'739px-Chest_Xray_PA_3-8-2010.png', 0.2)
plt.imshow(inference.img_with_masks( image, [mask[0], mask[1]], alpha = 0.1))
Results on data from the Internet
resnet34
densenet121
Authors
Renat Alimbekov, Ivan Vassilenko, Abylaikhan Turlassov
1 maintainer
Metadata
1 maintainer
Release files for lungs-segmentation 1.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| lungs_segmentation-1.1.2.tar.gz | 15.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| lungs_segmentation-1.1.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 31.5 kB
Release files / lungs_segmentation-1.1.2.tar.gz
| Download URL | lungs_segmentation-1.1.2.tar.gz |
|---|---|
| Size | 15.1 kB |
| Tags | Source |
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Release files / lungs_segmentation-1.1.2-py2.py3-none-any.whl
| Download URL | lungs_segmentation-1.1.2-py2.py3-none-any.whl |
|---|---|
| Size | 16.5 kB |
| Tags | Python 2 Python 3 |
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twine/3.3.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/49.2.0 requests-toolbelt/0.9.1 tqdm/4.28.1 CPython/3.7.3
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