diabetic_retinopathy_detection (Manual download)

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

diabetic_retinopathy_detection is configured with tfds.image.diabetic_retinopathy_detection.DiabeticRetinopathyDetectionConfig and has the following configurations predefined (defaults to the first one):

  • original (v2.0.0) (Size: 1.13 MiB): Images at their original resolution and quality.

  • 1M (v2.1.0) (Size: 1.13 MiB): Images have roughly 1,000,000 pixels, at 72 quality.

  • 250K (v2.1.0) (Size: 1.13 MiB): Images have roughly 250,000 pixels, at 72 quality.

  • btgraham-300 (v1.0.0) (Size: ?? GiB): 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.

diabetic_retinopathy_detection/original

Images at their original resolution and quality.

Versions:

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

WARNING: This dataset requires you to download the source data manually into manual_dir (defaults to ~/tensorflow_datasets/manual/diabetic_retinopathy_detection/): 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.

Statistics

Split Examples
ALL 88,712
TEST 42,670
TRAIN 35,126
VALIDATION 10,906
SAMPLE 10

Features

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),
})

Homepage

diabetic_retinopathy_detection/1M

Images have roughly 1,000,000 pixels, at 72 quality.

Versions:

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

WARNING: This dataset requires you to download the source data manually into manual_dir (defaults to ~/tensorflow_datasets/manual/diabetic_retinopathy_detection/): 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.

Statistics

Split Examples
ALL 88,712
TEST 42,670
TRAIN 35,126
VALIDATION 10,906
SAMPLE 10

Features

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),
})

Homepage

diabetic_retinopathy_detection/250K

Images have roughly 250,000 pixels, at 72 quality.

Versions:

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

WARNING: This dataset requires you to download the source data manually into manual_dir (defaults to ~/tensorflow_datasets/manual/diabetic_retinopathy_detection/): 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.

Statistics

Split Examples
ALL 88,712
TEST 42,670
TRAIN 35,126
VALIDATION 10,906
SAMPLE 10

Features

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),
})

Homepage

diabetic_retinopathy_detection/btgraham-300

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.

Versions:

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

WARNING: This dataset requires you to download the source data manually into manual_dir (defaults to ~/tensorflow_datasets/manual/diabetic_retinopathy_detection/): 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.

Statistics

None computed

Features

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),
})

Homepage

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"
}