mednet.data.classify.tbpoc¶
TB-POC dataset for computer-aided diagnosis.
This databases contain only the tuberculosis final diagnosis (0 or 1) and come from HIV infected patients.
Database reference: [GSVDP+18]
Important
Raw data organization
The TB-POC base datadir, which you should configure following the
Setup instructions, must contain at least the directory
TBPOC_CXR
with all JPEG images.
Data specifications:
Raw data input (on disk):
JPEG 8-bit Grayscale images
Original resolution (height x width or width x height): 2048 x 2500 pixels or 2500 x 2048 pixels
Total samples: 407
Output image:
Transforms:
Load raw grayscale jpeg with
PIL
Remove black borders
Convert to torch tensor
Torch center cropping to get square image
Final specifications:
Grayscale, encoded as a single plane tensor, 32-bit floats, square with varying resolutions (2048 x 2048 being the maximum), but also depending on black borders’ sizes on the input image.
Labels: 0 (healthy), 1 (active tuberculosis)
This module contains the base declaration of common data modules and raw-data loaders for this database. All configured splits inherit from this definition.
Module Attributes
Pythonic name of this database. |
|
Key to search for in the configuration file for the root directory of this database. |
Classes
|
TB-POC dataset for computer-aided diagnosis. |
A specialized raw-data-loader for the Shenzen dataset. |
- mednet.data.classify.tbpoc.DATABASE_SLUG = 'tbpoc'¶
Pythonic name of this database.
- mednet.data.classify.tbpoc.CONFIGURATION_KEY_DATADIR = 'datadir.tbpoc'¶
Key to search for in the configuration file for the root directory of this database.
- class mednet.data.classify.tbpoc.RawDataLoader[source]¶
Bases:
RawDataLoader
A specialized raw-data-loader for the Shenzen dataset.
- class mednet.data.classify.tbpoc.DataModule(split_path)[source]¶
Bases:
CachingDataModule
TB-POC dataset for computer-aided diagnosis.
- Parameters:
split_path (
Path
|Traversable
) – Path or traversable (resource) with the JSON split description to load.