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# Dataset Card for ImageNet (ILSVRC2012)

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## Dataset Details

### Dataset Description

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ImageNet (ILSVRC2012) is a large-scale dataset for visual recognition, consisting of 1,281,167 training images and 50,000 validation images across 1,000 object categories. The dataset was designed to facilitate large-scale image classification and object detection research.

### Dataset Sources

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- **Homepage:** https://www.image-net.org/challenges/LSVRC/2012/index.php
- **Paper:** Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., ... & Fei-Fei, L. (2015). Imagenet large scale visual recognition challenge. International journal of computer vision, 115, 211-252.

## Dataset Structure

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Total images: 1,331,167

Classes: 1000 categories

Splits:

- **Train:** 1,281,167 images

- **Validation:** 50,000 images

Image specs: Variable resolution, RGB

## Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
```
from datasets import load_dataset  

# Load the dataset  
dataset = load_dataset("randall-lab/imagenet", split="train", trust_remote_code=True)   
# dataset = load_dataset("randall-lab/imagenet", split="validation", trust_remote_code=True)  

# Access a sample from the dataset  
example = dataset[0]  
image = example["image"]  
label = example["label"]  

image.show()  # Display the image  
print(f"Label: {label}")
```

## Citation

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

@article{russakovsky2015imagenet,
  title={Imagenet large scale visual recognition challenge},
  author={Russakovsky, Olga and Deng, Jia and Su, Hao and Krause, Jonathan and Satheesh, Sanjeev and Ma, Sean and Huang, Zhiheng and Karpathy, Andrej and Khosla, Aditya and Bernstein, Michael and others},
  journal={International journal of computer vision},
  volume={115},
  pages={211--252},
  year={2015},
  publisher={Springer}
}