A fully user-side image search engine.

• Flickr does not provide an official similar image search engine nor corresponding API. Nevertheless, CLEAR realizes it on a user-side.
• CLEAR runs totally on a client side. It does not use a backend server at all.
• CLEAR does not store any images nor build search indices, while traditional search systems require to build search indices.

The paper describes CLEAR in detail.

arXiv: https://arxiv.org/abs/2206.08521

https://clear.joisino.net/

Interface of CLEAR. Upload an image, and then CLEAR retrieves similar images from Flickr. The functionality of CLEAR is simple. The highlight lies rather in how it is realized and how easy the deployment is.

$ git clone [email protected]:joisino/clear.git
$ cd clear
$ echo 'REACT_APP_FLICKR_KEY="0123456789abcdef"' > .env.local
$ npm install
$ npm start

Or you can try it with Docker.

$ git clone [email protected]:joisino/clear.git
$ cd clear
$ echo 'REACT_APP_FLICKR_KEY="0123456789abcdef"' > .env.local
$ docker run -it --rm -v $PWD:/app -p 13000:3000 -w /app -u node node /bin/bash -c "npm install && npm start"

Replace 0123456789abcdef with a Flickr API key. You can get a key at https://www.flickr.com/services/api/misc.api_keys.html. It takes a few minutes to get a key.

The feature extractor and score function are defined in src/score.js.

• getFeature computes feature vectors for both the source image and retrieved images. The embedding layer is defined in embeddingName. You can try other layers, e.g., 'module_apply_default/MobilenetV2/Logits/AvgPool'.
• embs2score computes scores. The higher the better. You can try other functions, e.g., the Gaussian kernel Math.exp(- emb1.squaredDifference(emb2).sum().dataSync()[0] / 1000).

As CLEAR does not rely on any backend servers or search indices, you can seamlessly use the system after you change the score function.

You can also change the search target from Flickr to other services by writing a wrapper in src/flickr.js.

@inproceedings{sato2022clear,
  author    = {Ryoma Sato},
  title     = {CLEAR: A Fully User-side Image Search System},
  booktitle = {The 31st {ACM} International Conference on Information
               and Knowledge Management, {CIKM}},
  year      = {2022},
}