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Check the traffic stats of Face Recognition on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Face Recognition on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Face Recognition's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Face Recognition on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about Face Recognition on Reddit. This can help you find out how popualr the product is and what people think about it.
Did you look at egoblur? Its a lot more effective at face detection than https://github.com/ageitgey/face_recognition granted, you'd have to do your own face matching to do exception. - Source: Hacker News / about 2 months ago
Syncthing, python face_recognition [1], a static gallery (sigal [2]), and a few lines of bash and its fully automatic. I can even share links with family. [1] https://github.com/ageitgey/face_recognition. - Source: Hacker News / 10 months ago
Camera connected to a PI? Something like this could run locally: https://github.com/ageitgey/face_recognition. Source: almost 2 years ago
One of the most common challenges is the black-box problem, when the pipeline becomes too complex to understand it would happen. This can make it difficult to identify issues with the system or to understand why it isn't working as we expected or make accurate predictions that saiwa company find out the solution for Face Recognition. Another challenge is the time required for organizations to deploy a machine... Source: over 2 years ago
Second link is an easy to implement python library is you want to build it yourself Https://github.com/ageitgey/face_recognition. Source: over 2 years ago
It is similar to https://github.com/ageitgey/face_recognition, except that Ageitgey's cli only compares the first face found in the image to the first one found the the second. Source: over 2 years ago
You'd have alot more luck with something like DLIB or an open source implementation such as: https://github.com/ageitgey/face_recognition. Source: over 2 years ago
To know more about face_recognition module https://github.com/ageitgey/face_recognition. - Source: dev.to / almost 3 years ago
Face_recognition - fairly easy install as long as dlib compiles for you. Should be able to get your face location ok. This is the older, most mature, but doesn't have as many features and might not have the accuracy of other models. Able to do face recognition. Source: almost 3 years ago
I'm trying to find an excellent library. Now I used https://github.com/ageitgey/face_recognition But it's detect face is not good. Source: almost 3 years ago
I would advice against using commercial face recognition APIs - they will probably cost money and you won't learn too much from a programming point of view. Why not use something like https://github.com/ageitgey/face_recognition. Source: about 3 years ago
You could start with DLIB and Geitgey's Face Recognition. They are pretty off-the-shelf packages, which should run fine on a single Intel processor (considering it's not too old). Source: over 3 years ago
I tried https://github.com/ageitgey/face_recognition and https://github.com/esimov/pigo so far and they both work OK, but from there, you would need to add EXIF tags into your pictures, so they can be picked up by img-DB. Source: over 3 years ago
I want use this library: https://github.com/ageitgey/face_recognition. Its a python library based on https://dlib.net for face recognition. Source: over 3 years ago
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