Datasets:
Tasks:
Image Classification
Sub-tasks:
multi-label-image-classification
Languages:
English
Multilinguality:
monolingual
Size Categories:
n<1K
Language Creators:
found
Annotations Creators:
machine-generated
License:
Commit
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Parent(s):
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- **Repository: https://colab.research.google.com/drive/1EnqpDiKOVYhR0c6f4CgmDg2zqcbYZJpB#scrollTo=c1ef3d21-6e0e-46c9-a459-8a2ab856a5ca**
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- **Point of Contact: Kevin Leffew – kleffew94@gmail.com**
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### golf-course
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This dataset (bethecloud/golf-courses) includes 21 unique images of golf courses pulled from Unsplash.
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By using the golf course images as part of their training data, participants can fine-tune their models to recognize and classify specific features and elements commonly found on golf courses. The ultimate goal after the hackathon is to pull this dataset from decentralized cloud storage (like Storj DCS), increasing its accessibility, performance, and resilience by distributing across an edge of over 17,000 uncorrelated participants.
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# Usage
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The golf-courses dataset can be used by modifying the instance_prompt: a photo of golf course
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### Languages
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In the future, Storj DCS will be used to download large datasets (exceeding 1TB) in a highly parallel, highly performant, and highly economical manner (by utilizing a network of over 17,000 diverse and economically incentivized datacenter node endpoints.
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## Dataset Creation
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### Curation Rationale
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This model was created as a sample by Kevin Leffew as part of the DreamBooth Hackathon.
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Thanks to [John Whitaker](https://github.com/johnowhitaker) and [Lewis Tunstall](https://github.com/lewtun)for writing out and describing the initial hackathon parameters at https://huggingface.co/dreambooth-hackathon.
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- **Repository: https://colab.research.google.com/drive/1EnqpDiKOVYhR0c6f4CgmDg2zqcbYZJpB#scrollTo=c1ef3d21-6e0e-46c9-a459-8a2ab856a5ca**
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- **Point of Contact: Kevin Leffew – kleffew94@gmail.com**
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### Dataset Summary: golf-course
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This dataset (bethecloud/golf-courses) includes 21 unique images of golf courses pulled from Unsplash.
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By using the golf course images as part of their training data, participants can fine-tune their models to recognize and classify specific features and elements commonly found on golf courses. The ultimate goal after the hackathon is to pull this dataset from decentralized cloud storage (like Storj DCS), increasing its accessibility, performance, and resilience by distributing across an edge of over 17,000 uncorrelated participants.
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## Example Output
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![golf-acropolis.jpg]https://link.storjshare.io/juid5vc27dbajh6zyzplf4fah5xq/golf-course-output%2Fgolf-acropolis.png
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# Usage
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The golf-courses dataset can be used by modifying the instance_prompt: a photo of golf course
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### Languages
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In the future, Storj DCS will be used to download large datasets (exceeding 1TB) in a highly parallel, highly performant, and highly economical manner (by utilizing a network of over 17,000 diverse and economically incentivized datacenter node endpoints.
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### Curation Rationale
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This model was created as a sample by Kevin Leffew as part of the DreamBooth Hackathon.
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Thanks to [John Whitaker](https://github.com/johnowhitaker) and [Lewis Tunstall](https://github.com/lewtun)for writing out and describing the initial hackathon parameters at https://huggingface.co/dreambooth-hackathon.
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## Example Training Data
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