Note
This is a Hugging Face dataset. Learn how to load datasets from the Hub in the Hugging Face integration docs.
Dataset Card for predicted_labels#
These photos are used in the FiftyOne getting started webinar. The images have a prediction label where were generated by self-supervised classification through a OpenClip Model. https://github.com/thesteve0/fiftyone-getting-started/blob/main/5_generating_labels.py They were then manually cleaned to produce the ground truth label. https://github.com/thesteve0/fiftyone-getting-started/blob/main/6_clean_labels.md
They are 300 public domain photos taken from Flickr. They will be used to fine tune a model. They are purely for teaching purposes and are not recommended for any other use. No other guarantees provided.
This is a FiftyOne dataset with 300 samples.
Installation#
If you haven’t already, install FiftyOne:
pip install -U fiftyone
Usage#
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/getting-started-labeled-photos")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details#
Dataset Description#
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Language(s) (NLP): en
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Source Data#
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Bias, Risks, and Limitations#
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Recommendations#
Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.
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