mednet.data.classify.indian¶
Indian database for TB detection (a.k.a. Dataset A/Dataset B).
The Indian collection database has been established to foster research in computer-aided diagnosis of pulmonary diseases with a special focus on pulmonary tuberculosis (TB). This database is also known as the “Database A/Database B” database.
Important
Raw data organization
The Indian base datadir, which you should configure following the Setup instructions, must contain at least these two subdirectories:
DatasetA/
(directory containing the dataset A images in JPG format)DatasetB/
(directory containing the dataset B images in DICOM format)
Data specifications:
Raw data input (on disk):
JPG RGB 8-bit depth images with “inverted” grayscale scale, with varying resolution of at least 1024 x 1024 pixels per sample
Samples: 156 images and associated labels
Output image: Use the same transforms and specifications as for
classify.shenzhen
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
|
Indian database for TB detection (a.k.a. Dataset A/Dataset B). |
- mednet.data.classify.indian.DATABASE_SLUG = 'indian'¶
Pythonic name of this database.
- mednet.data.classify.indian.CONFIGURATION_KEY_DATADIR = 'datadir.indian'¶
Key to search for in the configuration file for the root directory of this database.
- class mednet.data.classify.indian.DataModule(split_path)[source]¶
Bases:
CachingDataModule
- Indian database for TB detection (a.k.a. Dataset A/Dataset B).
Names of the JSON files containing the splits to load for montgomery and shenzhen databases (in this order).
- Parameters:
split_path (
Path
|Traversable
) – Path or traversable (resource) with the JSON split description to load.