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license: apache-2.0
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---
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license: apache-2.0
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---
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# InkSight Small-p
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<div style="display: flex; gap: 10px; justify-content: left;">
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<a href="https://arxiv.org/abs/2402.05804">
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<img src="https://img.shields.io/badge/📄_Read_the_Paper-4CAF50?style=for-the-badge&logo=arxiv&logoColor=white" alt="Read the Paper">
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</a>
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<a href="https://github.com/google-research/inksight">
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<img src="https://img.shields.io/badge/View_on_GitHub-181717?style=for-the-badge&logo=github&logoColor=white" alt="View on GitHub">
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</a>
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<a href="https://research.google/blog/a-return-to-hand-written-notes-by-learning-to-read-write/">
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<img src="https://img.shields.io/badge/🌐_Google_Research_Blog-333333?style=for-the-badge&logo=google&logoColor=white" alt="Google Research Blog">
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</a>
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<a href="https://charlieleee.github.io/publication/inksight/">
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<img src="https://img.shields.io/badge/ℹ️_Info-FFA500?style=for-the-badge&logo=info&logoColor=white" alt="Info">
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</a>
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</div>
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## Example Usage
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```python
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from huggingface_hub import from_pretrained_keras
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import tensorflow_text
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model = from_pretrained_keras("Derendering/InkSight-Small-p")
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cf = model.signatures['serving_default']
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prompt = "Derender the ink." # "Recognize and derender." or "Derender the ink: <text>"
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input_text = tf.constant([prompt], dtype=tf.string)
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image_encoded = tf.reshape(tf.io.encode_jpeg(np.array(image)[:, :, :3]), (1, 1))
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output = cf(**{'input_text': input_text, 'image/encoded': image_encoded})
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```
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## Citation
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If you find our work useful for your research and applications, please cite using this BibTeX:
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```bibtex
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@article{mitrevski2024inksight,
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title={InkSight: Offline-to-Online Handwriting Conversion by Learning to Read and Write},
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author={Mitrevski, Blagoj and Rak, Arina and Schnitzler, Julian and Li, Chengkun and Maksai, Andrii and Berent, Jesse and Musat, Claudiu},
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journal={arXiv preprint arXiv:2402.05804},
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year={2024}
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}
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```
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