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Awesome presentation, thanks!

Very well explained! Thank you!

when i run code it says internal server error. how can i fix it

thank you for your demo

Hi. What did you click to access the link at 19:44? Please can you reply ASAP?

Sir, can i use this code on android studio apps? Its kinda mobile application

What algorithm is used? to process the searching

Hi I would like to build something similar with you demo. Is there any chance to discuss about a small project? Lmk!

Cool stuff.

Cool stuff

But is it possible to scale this up for lets say 1k images , wont it slow down?

very helpful video sir, but when i upload different data from datasets it showing results but i want is None as output

Awesome, You are the superb coder I ever seen, Thank you soo Very much

I was curious and googled your name, then found that in result page, wiki had introduced you as a baseball player 😆

Thanks Mr Matsui, it is a great video!

Is there a way to upgrade it that the results will show links of websites they are extracted from

How to run

If I want to apply and check the performance of different models then How can I do it?

Fast api

How to use Django instead of Flask?

At 11:44, dist = q_norms[m] + x_norms[n] - **2** x ip[m][n]? Shouldn't ip[m][n] be multiplied by 2 (to match the formula on the top of the slide)?

Thank you for your explanation!

Thank you! That is awesome.

I expect that we can do better than kmeans clustering for dimension reduction and coarse quantization, for image data at least, by smart feature detection using transfer learning like ResNet50 as main body, plus VAE as head of network for smart dimension reduction. Also use built-in tensor quantization on the short vector, or build your own quantizer that is differentiable for purpose of backprop by custom sequential Relu activations that start at zero, which is stabdard relu, then 1,2,3,... Until it swept entire 8 bit range ie 256, or 16 bit range ie 16k. No more fine search is needed consequently, just direct addressing to correct hash bucket, and pull out an item from its list. Or you can search fine list other ways like pq or lsh .

This presentation is great. I love it! It's a fast way to understand the summary of the state of the art of large scale search.

Can you create a data base like this for me? I would pay

Really very nice project and easy to run and learn and hasslefree

Thank you so much.

Brilliant Project !!

Thank you !!! very clear

Thank you for the demo, very helpful!

I have an app built in react native using javascript. Is there a library like this that I can use in my app? I would like to have it looks up local storage for images not online.

The submit query button is showing all my images data....not the related images as query Can anyone help....

On simple-image-search.xyz do you have millions of image in your static/img database ??

Heyyy, please help me. How can I make this without having to own 100 images. can't I use Imagenet's API or something to show results online ? I want to deploy this on heroku but don't want to put all the millions of images in my img folder

Daiiiiiisukiii

Thank you for such a great video I really enjoyed it

I love you

Very well explained topic. And a great presentation as well with nice colors for the hashing function and visual on the coarse graph to fine graph slide. Thanks so much

This is fantastic. Thank you so much for posting this. This is easy to follow and it works exactly as expected. Great job!

Thank you for a great summary!

ありがろうまついせいんせい

An excellent work.