[null,null,["最終更新日 2022-12-06 UTC。"],[],[],null,["# diabetic_retinopathy_detection\n\n\u003cbr /\u003e\n\n| **Warning:** Manual download required. See instructions below.\n\n- **Description**:\n\nA large set of high-resolution retina images taken under a variety of imaging\nconditions.\n\n- **Additional Documentation** :\n [Explore on Papers With Code\n north_east](https://paperswithcode.com/dataset/diabetic-retinopathy-detection-dataset)\n\n- **Homepage** :\n \u003chttps://www.kaggle.com/c/diabetic-retinopathy-detection/data\u003e\n\n- **Source code** :\n [`tfds.image_classification.DiabeticRetinopathyDetection`](https://github.com/tensorflow/datasets/tree/master/tensorflow_datasets/image_classification/diabetic_retinopathy_detection.py)\n\n- **Versions**:\n\n - **`3.0.0`** (default): New split API (\u003chttps://tensorflow.org/datasets/splits\u003e)\n- **Download size** : `1.13 MiB`\n\n- **Manual download instructions** : This dataset requires you to\n download the source data manually into `download_config.manual_dir`\n (defaults to `~/tensorflow_datasets/downloads/manual/`): \n\n You have to download this dataset from Kaggle.\n \u003chttps://www.kaggle.com/c/diabetic-retinopathy-detection/data\u003e\n After downloading, unpack the test.zip file into test/ directory in manual_dir\n and sample.zip to sample/. Also unpack the sampleSubmissions.csv and\n trainLabels.csv.\n\n- **Auto-cached**\n ([documentation](https://www.tensorflow.org/datasets/performances#auto-caching)):\n No\n\n- **Splits**:\n\n| Split | Examples |\n|----------------|----------|\n| `'sample'` | 10 |\n| `'test'` | 42,670 |\n| `'train'` | 35,126 |\n| `'validation'` | 10,906 |\n\n- **Feature structure**:\n\n FeaturesDict({\n 'image': Image(shape=(None, None, 3), dtype=uint8),\n 'label': ClassLabel(shape=(), dtype=int64, num_classes=5),\n 'name': Text(shape=(), dtype=string),\n })\n\n- **Feature documentation**:\n\n| Feature | Class | Shape | Dtype | Description |\n|---------|--------------|-----------------|--------|-------------|\n| | FeaturesDict | | | |\n| image | Image | (None, None, 3) | uint8 | |\n| label | ClassLabel | | int64 | |\n| name | Text | | string | |\n\n- **Supervised keys** (See\n [`as_supervised` doc](https://www.tensorflow.org/datasets/api_docs/python/tfds/load#args)):\n `None`\n\n- **Citation**:\n\n @ONLINE {kaggle-diabetic-retinopathy,\n author = \"Kaggle and EyePacs\",\n title = \"Kaggle Diabetic Retinopathy Detection\",\n month = \"jul\",\n year = \"2015\",\n url = \"https://www.kaggle.com/c/diabetic-retinopathy-detection/data\"\n }\n\ndiabetic_retinopathy_detection/original (default config)\n--------------------------------------------------------\n\n- **Config description**: Images at their original resolution and quality.\n\n- **Dataset size** : `89.15 GiB`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\ndiabetic_retinopathy_detection/1M\n---------------------------------\n\n- **Config description**: Images have roughly 1,000,000 pixels, at 72 quality.\n\n- **Dataset size** : `3.96 GiB`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\ndiabetic_retinopathy_detection/250K\n-----------------------------------\n\n- **Config description**: Images have roughly 250,000 pixels, at 72 quality.\n\n- **Dataset size** : `1.30 GiB`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples... \n\ndiabetic_retinopathy_detection/btgraham-300\n-------------------------------------------\n\n- **Config description**: Images have been preprocessed as the winner of the\n Kaggle competition did in 2015: first they are resized so that the radius of\n an eyeball is 300 pixels, then they are cropped to 90% of the radius, and\n finally they are encoded with 72 JPEG quality.\n\n- **Dataset size** : `3.65 GiB`\n\n- **Figure**\n ([tfds.show_examples](https://www.tensorflow.org/datasets/api_docs/python/tfds/visualization/show_examples)):\n\n- **Examples** ([tfds.as_dataframe](https://www.tensorflow.org/datasets/api_docs/python/tfds/as_dataframe)):\n\nDisplay examples..."]]