Hacker Newsnew | past | comments | ask | show | jobs | submit | szidev's commentslogin

Hey thanks! Glad you like it.


Great suggestion. I'll try and get that added in today. I was debating adding in score checkpoints that unlock other permutations, but I might just add in a shuffle and make sure it doesn't reveal the wotd. Thanks for the feedback!


Great callout. I forgot to update the help modal when I put in that 3 letter minimum. Sorting is a great idea, too. Thanks for the feedback!

Edit: Both things added in. I appreciate ya!


Excellent!


Alyssa is such an inspiring individual. I'm glad she's working on the things that interest her.


Not the A variant, which is what USAF flies.


not every tp-link model (or revision, or locale, or firmware version) that shares a web interface with the c7 requires you to manually set a password. even if that were the case, there are bound to be users who aren't security savvy and chose a very weak password (e.g. "password", "admin").

many tp-link routers also have configurable vpn servers built in, which can open up the whole network to malicious actors.


I know you're joking, but someone has actually done that: https://www.theatlantic.com/technology/archive/2011/03/antar...


What a great writeup! It's awesome to see the process all the way from component selection, through code, to a final working demo. I'm definitely saving this for when I have time to do more hands-on FPGA learning.


Great write-up! We did something very similar when trying to find duplicate product images for a consumer review site we were working on. Our implementation desaturated the image, broke it into a fixed number of tiles, and generated a histogram of each tile's values. Then we put a threshold on the histogram values, and had each value in the tile represent a bit. Combine the bits, and we had a hash to store in the DB. Our hashes were a bit larger, so images within a certain hamming distance were flagged, rather than just looking for exact hash matches. It took quite a bit of tuning for us to get good results, but it seemed to work pretty well. Do you see many false positives with such a small processed image size (the 9x8 one, I mean)?


In practice we are using an image size of 17x16 which will result in a hash size of 256 bits and currently it seems to work pretty well. I ran the algorithm through the whole dataset (about 330.000+ icons) and I would say that from all the duplicate matches about 1% where false positives.

Also, we will be integrating this into the reviewing process for an iconset, where we also do a manual quality check, showing possible matches to something currently uploaded so skimming over one or two false positives isn't such a big deal and we where more interested in the speed of the algorithm.


That's pretty impressive performance given the hash size and speed. Thanks for sharing!


great idea. i'll have to keep this in mind for future projects.


Guidelines | FAQ | Lists | API | Security | Legal | Apply to YC | Contact

Search: