Plausible.io VS Dlib
Compare Plausible.io VS Dlib and see what are their differences
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Plausible.io
Google Analytics
Fathom Analytics
Matomo
Simple Analytics
umami
Mixpanel
PostHog
Dlib
OpenCV
PyTorch
Face Recognition
Scikit Image
TensorFlow
SimpleCV
Kaldi ASR
Plausible Analytics is not designed to be a clone of Google Analytics. It is meant as a simple-to-use replacement and a privacy-friendly alternative that can help many site owners.
It's quick, simple to use and understand with all the metrics displayed on one page. Doesn't track hundreds of metrics like Google Analytics does
Lightweight script of less than 1 KB so sites load fast. The script is 45 times smaller script than the Google Analytics one
Doesn't use cookies so there's no need to worry about cookie banners
Doesn't track personal data so it's compliant with GDPR out of the box and you don't need to worry about asking for data consent
It's open source with the code available on GitHub so you can even self host exactly the same product free as in beer
Unlike Google Analytics, the cloud product is not free as in beer because the business model is subscriptions rather than selling the data of your visitors. Plausible Analytics is bootstrapped without any external funding so the subscription fees help cover the costs and time spent on development.
Plausible.ioI've been using plausible since Sep 2019 and never had any doubts about it. It provides me with everything I need related to visitor stats while keeping privacy in first place.
It doesn't slow down my website loading speed (it's amazing, it's less than 1KB in size!), is not blocked by adblockers since it's not really a tracker tracker, and owners are super cool and they actually respond to every inquiry you could possibly have.
If you're looking for de-googling your stuff, you can start with Plausible :)
I tried several analytics tools prior to Plausible, namely Google Analytics and later on Matomo. I found both to be fairly complicated for my usage which is a personal blog. Complicated in the way I had to install and use them. Plausible's simple to set up approach combined with a very clean and inviting user interface was a breath of fresh air. It's simple and clean enough that it actually makes me want to check and analyse my traffic which is a feeling I never thought I'd have having tried alternatives.
It offers clear information about what I really need, without distractions, without advertising and does not slow my site.
Based on our record, Plausible.io seems to be a lot more popular than Dlib. While we know about 216 links to Plausible.io, we've tracked only 17 mentions of Dlib. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Side note: thereโs plenty of Analytics tools that donโt require cookies. Plausible (https://plausible.io) is one of them, there are many others. - Source: Hacker News / 14 days ago
Also a small tooling aside โ if you're tracking how often skills get used across your team (or just want analytics on your dev blog without the GDPR cookie banner dance), privacy-focused options like Umami or Plausible give you full data ownership and a much lighter footprint than Google Analytics. I migrated two side projects to Umami last year and haven't looked back. - Source: dev.to / 3 months ago
So this post is about something I've been chewing on for months but finally moved on: ripping Google Analytics out of three side projects and picking a privacy-focused alternative. Specifically, I'll compare Umami, Plausible, and Fathom โ the three I actually evaluated โ and walk through the migration steps that worked for me. - Source: dev.to / 3 months ago
Plausible is what I recommend when someone wants to set it up and forget about it. It's an EU-based company, the data stays in the EU, and they're very transparent about their infrastructure. - Source: dev.to / 4 months ago
Plausible is also open-source with a self-hosted option, but their cloud-hosted product is where most people land. It's polished, opinionated, and genuinely pleasant to use. - Source: dev.to / 4 months ago
The apparent gender estimates from photos are using dlib, and I really ought to get what I'm doing cleaned up in such a way that other people can use it easily. Source: over 3 years ago
Additionally, C++ may be used for extremely high levels of optimization even for cloud-based ML. Dlib and Kaldi are C++ libraries used as dependencies in Python codebases for computer vision and audio processing, for example. So if your application requires you to customize any functions similar to those libraries, then you'll need C++ knowhow. Source: over 3 years ago
If you know C++, you don't need anything else. Go and learn APIs for C++ libraries. If you're into DSP, why not study Dlib?. Source: over 3 years ago
The data is mostly in this spreadsheet. The apparently facial gender estimates are made with Dlib. The mental health assessments are from Beck's Depression Inventory and the Snaith-Hamilton Pleasure Scale. The graph is made with gnuplot. Source: over 3 years ago
The plugin uses dlib library with a very fast HOG detector for both face recognition and detector following the relative examples. Source: almost 4 years ago
Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.
OpenCV - OpenCV is the world's biggest computer vision library
Fathom Analytics - Simple, trustworthy website analytics (finally)
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Matomo - Matomo is an open-source web analytics platform
Face Recognition - Face Recognition is an app that is used for testing different facial recognition methods such as Caffe and Neural Networks to name a few.