This can be done with OpenCV and some custom code in C or python, (it is not a very common requirement).
The answers to this question do a great job of discussing how to go about this in C.
For a ready rolled solution you might wish to take a look at NEFI:
OpenCV includes mechanisms that can be used to detect people in a view as in https://www.pyimagesearch.com/2015/11/09/pedestrian-detection-opencv/ it is:
Free, Gratis & Open Source
A set of C++ libraries & Bindings
Basically what you are looking for was developed as Sikuli by the Sikuli Lab at the University of Colorado Boulder and is now maintained and further developed as SikuliX by RaiMan and the open source community.
It is free, gratis & open source (MIT Licenced) and provides:
Search the Desktop visually for specific components & events
Interact with ...
Mathematica has a built-in function called MorphologicalGraph.
The open source image analysis software Fiji can do this too. The rough steps are:
Smoothen the image if needed
Threshold the image to make it binary
Process -> Binary -> Skeletonize
Analyze -> Skeleton -> Analyze Skeleton, tick Show Detailed Info. When a table comes up, save it as CSV.
You can indeed do this sort of task with a Raspberry Pi, Python and OpenCV there are a number of write-ups on how to do this on the PyImageSearch site such as https://www.pyimagesearch.com/2017/02/13/recognizing-digits-with-opencv-and-python/ (dealing with number recognition) and https://www.pyimagesearch.com/2018/08/20/opencv-text-detection-east-text-...
There are some programs that work decently enough. Unfortunately, one of them is (I think) no longer under development. It is a pity.
VisiPics rates the similarity using colors. http://www.visipics.info/index.php?title=Main_Page
Pixiple give you also similar images, this can be handy to detect the same image with some changes in cropping or rotation but ...
What you are describing was developed in 1966 by a real estate investor and uses simple math to determine vehicle speed and was known as VASCAR. I can attest from experience that one can measure time passed during a one-quarter mile traverse and divide 3600 by the number of seconds to get the speed over that distance. Of course, one would want to maintain a ...
Looks like Aipoly does offline image recognition of basic objects. It is marketed for accessibility needs so I imagine if there are other apps like this one it might be easier to search for them by adding 'accessibility' to your search terms.
OpenCV can detect faces and/or upright people and has examples of doing both. It can be used from C/C++/python and is open source & cross platform.
While it is not a ready made solution it can be used to construct such solutions as can be seen with the examples of pedestrian detection & face detection presumably you would need to do both to build a ...
If you have a static positioned webcam, you can use Linux as an os with the program "motion" - it detects changes in the webcam view, and then can run a script when motion is detected. Lots of other options like sensitivity level, watching only a certain area of the image for change, how long change must be taking place from reference frame for it to be ...
On the Tensorflow Github site there are pretrained models, some of which are based on Image collections. I think with some digging you'll find more.
Here is one available as a NodeJS model: MobileNet - Classify images with labels from the ImageNet database.
`npm i @tensorflow-models/mobilenet`
I haven't used it personally though. A while back, at a ...
If you using Android than also go for OpenCV in android that will helps you a lot and provide flexibility
Would the Picture edition of DupeGuru be sufficient? The tool allows you to specify multiple directories, say, one containing your collection and another with the search candidate, so this would seem to come close to your requirements.
Though it is meant to find/remove (near)duplicates of images, it initially displays a list of the possible matches which ...
[Disclaimer: i work for Moodstocks]
You should have a look at the Moodstocks SDK. It fits most of your requirements:
it's robust to lightning and perspective changes,
it tolerates partial occlusion, for example by fingers,
it require no training at all: you just upload (index) an image to make it instantly recognizable,
it's extremely fast: the image ...
There is no such application in Play Store as far as I know. I've searched myself for half an hour and couldn't find an application with that concept. You should probably ask/request a android developer to make an app like this in some forums say XDA Developers.
[Alternative solution] - Only a suggestion from my side that you may have already tried. Take the ...