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README.md
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## Intended Use and Evaluation
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- Samples: for display and qualitative understanding; not for model training.
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- Protected: for local algorithms to run against machine-readable features.
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- Evaluation: submit results (e.g., `submission.json`) for scoring against hidden GroundTruth.
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## Quick Start (How Others Can Load This Dataset)
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Install dependency:
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```bash
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pip install datasets
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```
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Load from local script (before upload):
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```python
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from datasets import load_dataset
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# samples mode
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samples = load_dataset("./photobench.py", "samples", trust_remote_code=True)
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print(samples["test"][0])
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# protected mode
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protected = load_dataset("./photobench.py", "protected", trust_remote_code=True)
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print(protected["test"][0])
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```
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Load from Hugging Face Hub (after upload):
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```python
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from datasets import load_dataset
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# replace with your real repo id
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samples = load_dataset("your-hf-username/PhotoBench", "samples", trust_remote_code=True)
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protected = load_dataset("your-hf-username/PhotoBench", "protected", trust_remote_code=True)
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```
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Dataset page URL (after upload):
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```text
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https://huggingface.co/datasets/your-hf-username/PhotoBench
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```
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If YAML front matter is valid and files are uploaded correctly, the Hub will show a dataset page with viewer tabs for available configs.
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For privacy and compliance notes, refer to the project’s instruction documents.
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## Intended Use and Evaluation
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- Samples: for display and qualitative understanding; not for model training.
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- Protected: for local algorithms to run against machine-readable features.
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- Evaluation: submit results (e.g., `submission.json`) for scoring against hidden GroundTruth.
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