CLIPSE -- a minimalistic CLIP-based image search engine for research
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Abstract (arXiv)
A brief overview of CLIPSE, a self-hosted image search engine with the main application of research, is provided. In general, CLIPSE uses CLIP embeddings to process the images and also the text queries. The overall framework is designed with simplicity to enable easy extension and usage. Two benchmark scenarios are described and evaluated, covering indexing and querying time. It is shown that CLIPSE is capable of handling smaller datasets; for larger datasets, a distributed approach with several instances should be considered.
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References · 3
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,152
- 2022Reproducible scaling laws for contrastive language-image learningcited by 1,173
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