The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: RuntimeError
Message: Dataset scripts are no longer supported, but found country211.py
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1167, in dataset_module_factory
raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
RuntimeError: Dataset scripts are no longer supported, but found country211.pyNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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} }
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