# ImageNet 2012
The ImageNet 2012 dataset.
ImageNet, as known as ILSVRC 2012, is an image dataset organized according
to the WordNet hierarchy. Each meaningful concept in WordNet, possibly
described by multiple words or word phrases, is called a “synonym set” or
“synset”. There are more than 100,000 synsets in WordNet, majority of them
are nouns (80,000+). ImageNet provides on average 1,000 images to
illustrate each synset. Images of each concept are quality-controlled and
human-annotated. In its completion, we hope ImageNet will offer tens of
millions of cleanly sorted images for most of the concepts in the WordNet
hierarchy.
Note that labels were never publicly released for the test set, so only the
training and validation sets are provided.
#### NOTE
In order to load the ImageNet dataset, you must download the source data
manually. The directory should be organized in the following format:
```text
source_dir/
ILSVRC2012_devkit_t12.tar.gz # both splits
ILSVRC2012_img_train.tar # train split
ILSVRC2012_img_val.tar # validation split
```
You can register at [http://www.image-net.org/download-images](http://www.image-net.org/download-images) in order to
get links to download the data.
**Details**
- Dataset name: `imagenet-2012`
- Dataset source: [http://image-net.org](http://image-net.org)
- Dataset license: [https://image-net.org/download](https://image-net.org/download)
- Dataset size: 144.02 GB
- Tags: `image, classification, manual`
- Supported splits: `train, validation`
- ZooDataset classes:
- [`ImageNet2012Dataset`](../../api/fiftyone.zoo.datasets.tf.md#fiftyone.zoo.datasets.tf.ImageNet2012Dataset) (TF backend)
- [`ImageNet2012Dataset`](../../api/fiftyone.zoo.datasets.torch.md#fiftyone.zoo.datasets.torch.ImageNet2012Dataset) (Torch backend)
#### NOTE
You must have the
[Torch or TensorFlow backend(s)](../api.md#dataset-zoo-ml-backend) installed to
load this dataset.
**Example usage**
Python
CLI
```python
import fiftyone as fo
import fiftyone.zoo as foz
# The path to the source files that you manually downloaded
source_dir = "/path/to/dir-with-imagenet-files"
dataset = foz.load_zoo_dataset(
"imagenet-2012",
split="validation",
source_dir=source_dir,
)
session = fo.launch_app(dataset)
```
```shell
# The path to the source files that you manually downloaded
SOURCE_DIR="/path/to/dir-with-imagenet-files"
fiftyone zoo datasets load imagenet-2012 --split validation \
--kwargs "source_dir=${SOURCE_DIR}"
fiftyone app launch imagenet-2012-validation
```
