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diabetic_retinopathy_detection

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  • Description:

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

Split Examples
'sample' 10
'test' 42,670
'train' 35,126
'validation' 10,906
  • Feature structure:
FeaturesDict({
    'image': Image(shape=(None, None, 3), dtype=uint8),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=5),
    'name': Text(shape=(), dtype=object),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
image Image (None, None, 3) uint8
label ClassLabel int64
name Text object
@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.

  • Dataset size: 89.15 GiB

  • Figure (tfds.show_examples):

Visualization

diabetic_retinopathy_detection/1M

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

  • Dataset size: 3.96 GiB

  • Figure (tfds.show_examples):

Visualization

diabetic_retinopathy_detection/250K

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

  • Dataset size: 1.30 GiB

  • Figure (tfds.show_examples):

Visualization

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.

  • Dataset size: 3.65 GiB

  • Figure (tfds.show_examples):

Visualization