Quiltnet B 16

🚀 QuiltNet-B-16

QuiltNet-B-16 is a CLIP ViT-B/16 vision - language foundation model. It's trained on the Quilt - 1M dataset from representative histopathology videos. This model can handle various vision - language processing tasks like cross - modal retrieval, image classification, and visual question answering. It sets new records on many standard datasets and outperforms previous VLP methods.

🚀 Quick Start

The model can be directly used for zero - shot image classification, image and text retrieval. For more complex tasks, it can be used for image classification fine - tuning, linear probe image classification, image generation guiding and conditioning.

✨ Features

• Versatile VLP Tasks: Capable of performing cross - modal retrieval, image classification, and visual question answering.
• State - of - the - Art Performance: Establishes new state of the art on a wide range of standard datasets, outperforming prior VLP approaches.

📚 Documentation

Model Description

QuiltNet - B - 16 is a CLIP ViT - B/16 vision - language foundation model trained on the Quilt - 1M dataset curated from representative histopathology videos. It can perform various vision - language processing (VLP) tasks such as cross - modal retrieval, image classification, and visual question answering. QuiltNet establishes new state of the art in a wide range of standard datasets, and substantially outperforms prior VLP approaches:

Uses

Intended Use

The model is intended as a research output for research communities. We hope that this model will enable researchers to better understand and explore zero - shot, arbitrary image classification. We also hope it can be used for interdisciplinary studies of the potential impact of such models.

• Primary intended users: AI researchers.
• Primary uses: Researchers use the model to better understand robustness, generalization, and other capabilities, biases, and constraints of computer vision histopathology models.

Out - of - Scope Use Cases

• Deployment: Any deployed use case of the model - whether commercial or not - is currently out of scope.
• Non - deployed use in constrained environment: Non - deployed use cases such as image search in a constrained environment are not recommended unless there is thorough in - domain testing of the model with a specific, fixed class taxonomy.
• Language limitation: Since the model has not been purposefully trained in or evaluated on any languages other than English, its use should be limited to English language use cases.

Training Data

This model was trained with QUILT - 1M, an image - text dataset for histopathology. Curated from educational videos on Youtube, QUILT - 1M contributes the largest dataset for vision language modeling in histopathology.

⚠️ Important Note

The motivation behind dataset creation is to democratize research and experimentation around large - scale multi - modal model training and handling of uncurated, large - scale histopathology datasets crawled from publicly available internet. Our recommendation is therefore to use the dataset for research purposes.

Evaluation

Evaluation was done with code in the [CLIP Benchmark suite](https://github.com/LAION - AI/CLIP_benchmark), and results can be found in the paper on a list of varying histology tasks and datasets.

Disclaimer

It is important to note that the results obtained from this function are not intended to constitute medical advice or replace consultation with a qualified medical professional. The use of this function is solely at your own risk and should be consistent with applicable laws, regulations, and ethical considerations. We do not warrant or guarantee the accuracy, completeness, suitability, or usefulness of this function for any particular purpose, and we hereby disclaim any liability arising from any reliance placed on this function or any results obtained from its use.

Privacy

In accordance with the privacy policy of Youtube, only Video IDs data is redistributed by us. It is strictly prohibited to redistribute any content apart from the Video IDs. Any distribution carried out must adhere to the laws and regulations applicable in your jurisdiction, including export control laws and embargoes.

📄 License

This project is licensed under the MIT license.

📚 Citation

@misc{ikezogwo2023quilt1m,
      title={Quilt-1M: One Million Image-Text Pairs for Histopathology}, 
      author={Wisdom Oluchi Ikezogwo and Mehmet Saygin Seyfioglu and Fatemeh Ghezloo and Dylan Stefan Chan Geva and Fatwir Sheikh Mohammed and Pavan Kumar Anand and Ranjay Krishna and Linda Shapiro},
      year={2023},
      eprint={2306.11207},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}