diabetic_retinopathy_detection

• Description:

A large set of high-resolution retina images taken under a variety of imaging conditions.

• Homepage: https://www.kaggle.com/c/diabetic-retinopathy-detection/data

• Source code: tfds.image_classification.DiabeticRetinopathyDetection

• Versions:

  • 3.0.0 (default): New split API (https://tensorflow.org/datasets/splits)

• Download size: 1.13 MiB

• Dataset size: Unknown size

• Manual download instructions: This dataset requires you to download the source data manually into download_config.manual_dir (defaults to ~/tensorflow_datasets/downloads/manual/):
  You have to download this dataset from Kaggle. https://www.kaggle.com/c/diabetic-retinopathy-detection/data After downloading, unpack the test.zip file into test/ directory in manual_dir and sample.zip to sample/. Also unpack the sampleSubmissions.csv and trainLabels.csv.

• Auto-cached (documentation): Unknown

• Splits:

Split	Examples
'sample'	10
'test'	42,670
'train'	35,126
'validation'	10,906

• Feature structure:

FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=tf.uint8),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=5),
    'name': Text(shape=(), dtype=tf.string),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
image	Image	(None, None, 3)	tf.uint8
label	ClassLabel		tf.int64
name	Text		tf.string

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe): Missing.

• Citation:

@ONLINE {kaggle-diabetic-retinopathy,
    author = "Kaggle and EyePacs",
    title  = "Kaggle Diabetic Retinopathy Detection",
    month  = "jul",
    year   = "2015",
    url    = "https://www.kaggle.com/c/diabetic-retinopathy-detection/data"
}

diabetic_retinopathy_detection/original (default config)

• Config description: Images at their original resolution and quality.

diabetic_retinopathy_detection/1M

• Config description: Images have roughly 1,000,000 pixels, at 72 quality.

diabetic_retinopathy_detection/250K

• Config description: Images have roughly 250,000 pixels, at 72 quality.

diabetic_retinopathy_detection/btgraham-300

• Config description: Images have been preprocessed as the winner of the Kaggle competition did in 2015: first they are resized so that the radius of an eyeball is 300 pixels, then they are cropped to 90% of the radius, and finally they are encoded with 72 JPEG quality.