Dataset Card for Country211

Dataset Details

Dataset Description

The Country211 dataset is designed for country classification based on images. It was created to evaluate the geolocation capabilities of machine learning models. The dataset is a filtered subset of the YFCC100m dataset, consisting of images that have GPS coordinates corresponding to an ISO-3166 country code. The dataset is balanced, containing 150 training images, 50 validation images, and 100 test images for each of the 211 countries and territories.

Dataset Sources

• Homepage: https://github.com/openai/CLIP/blob/main/data/country211.md
• Paper: Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., ... & Sutskever, I. (2021, July). Learning transferable visual models from natural language supervision. In International conference on machine learning (pp. 8748-8763). PmLR.

Dataset Structure

Each sample in the dataset contains:

• image: A variable-sized RGB image

• label: An integer between 0 and 210, representing the country

Total images: 211 * (150 + 50 + 100) = 63,300

Classes: 211 (each corresponding to a country or territory)

Splits:

• Train: 150 images per country (31,650 total)

• Validation: 50 images per country (10,550 total)

• Test: 100 images per country (21,100 total)

Image specs: Variable sizes, 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/country211", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/country211", split="validation", trust_remote_code=True)   
# dataset = load_dataset("randall-lab/country211", split="test", 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

BibTeX:

@inproceedings{radford2021learning, title={Learning transferable visual models from natural language supervision}, author={Radford, Alec and Kim, Jong Wook and Hallacy, Chris and Ramesh, Aditya and Goh, Gabriel and Agarwal, Sandhini and Sastry, Girish and Askell, Amanda and Mishkin, Pamela and Clark, Jack and others}, booktitle={International conference on machine learning}, pages={8748--8763}, year={2021}, organization={PmLR} }