---
dataset_info:
  features:
  - name: img
    dtype: image
  - name: label
    dtype:
      class_label:
        names:
          '0': airplane
          '1': automobile
          '2': bird
          '3': cat
          '4': deer
          '5': dog
          '6': frog
          '7': horse
          '8': ship
          '9': truck
  splits:
  - name: train
    num_bytes: 1560708615.0
    num_examples: 190000
  - name: test
    num_bytes: 82238790.0
    num_examples: 10000
  download_size: 1642628895
  dataset_size: 1642947405.0
---

CIFARNet contains 200K images sampled from ImageNet-21K (Winter 2019 release), resized to 64x64, using coarse-grained labels that roughly match those of CIFAR-10. The exact ImageNet synsets used were:
```
{
  "n02691156": 0,  # airplane
  "n02958343": 1,  # automobile
  "n01503061": 2,  # bird
  "n02121620": 3,  # cat
  "n02430045": 4,  # deer
  "n02083346": 5,  # dog
  "n01639765": 6,  # frog
  "n02374451": 7,  # horse
  "n04194289": 8,  # ship
  "n04490091": 9,  # truck
}
```
The classes are balanced, and the dataset is pre-split into a training set of 190K images and a validation set of 10K images.