I’ve bought a Husky lens recently. It was very cheap for what you get.
(50 Euro’s) The first tests are promising.
Nice little, but powerful gadget.
Cables to connect Rpi or Arduino, mounts, Huskylens and Protectioncover (sold separately)
face recognition object tracking object recognition line tracking color recognition tag recognition object classification
Communication can be done via I2C and Uart.
Uses a sdcard to store learning data. Has white leds for object lighting.
Build-in objects which are recognised out of the box. (Others can be learned by the device)
aeroplane, bicycle, bird, boat, bottle, bus, car, cat, chair, cow, dining-table, dog, horse, motorbike, person, potted plant, sheep, sofa, train, TV
A few years ago i wrote a photo manager .. again .. ( see post about my
first previous photo manager ) It is a web gui to find photos in my huge photo archive. I manually added 190k tags to 120k photos in 20+ years.
I thought wouldn’t it be nice if i can generate additional metadata using Machine Learning. A few years ago i did some testing and followed a podcast and free course about machine learning.
So today i started to implement a addition to my gui. Machine recognition tags!
It already kinda works.
Things to do :
Make it a background job, my fileserver doesn’t run Tensorflow on a GPU, so it is slooow Embed in existing GUI and stats Design a editor to remove wrong tags
Below a part of ML images
Command to get a thumbnail sheet with only directory names:
montage -verbose -units PixelsPerInch -density 300 -tile 7x6 -label "%d" -font Arial -pointsize 6 -background "#FFFFFF" -fill "black" -define jpeg:size=253x154 -geometry 253x154+2+2 -auto-orient */*.JPG -title "ML Thumbs" thumbsheet.jpg
Maybe, i can use debug output like below.
['lakeside, lakeshore (score = 0.47934)', 'seashore, coast, seacoast, sea-coast (score = 0.11385)', 'sandbar, sand bar (score = 0.08822)', 'breakwater, groin, groyne, mole, bulwark, seawall, jetty (score = 0.06281)', 'valley, vale (score = 0.01790)', '']
I used OpenCV to track my face, and draw something that moves with me when i move.
Just a prove of concept. I will post used code when i find it back.
Today i started with Coursera’s Machine Learning course.
My friend aloha is doing interesting stuff with ML, but recently i’ve been interested in a work related ML project.
Besides this course i’m following a spotify Podcast called “Machine Learning Guide”, i listen to this on my way to work and back.
I’ve been playing with a lot of code after that. Luckily there are many ebooks about this subject.
One of the first was a python program wich used the length of a person and shoesize to determine if it was a man or a woman Another fun one was a program with could determine if a wine was red or white only based by a description There are several graphic based programs i’ve tried. Deepfake, 8mm film enhancers, image classifiers, openface For sound there was voice cloner to test. And audio to text (which i used to transcribe old cassette tapes and VHS tapes.
UPDATE: In 2022 i used what i have learned to enrich my photo metadata.