So this is the real deal if you want to be cool. I abandoned the stupid idea of creating a browser from scratch that can barely run GitHub or even play some videos on YouTube and decided to focus on good stuff. That’s when I decided to learn more about audio processing with Juce. My friend Julia Kaffka sent me a link about some Python library from Spotify that was created for musicians or producers.

Just about to call it a day, I must say to you people I am trying to build a browser from scratch. And it seems to work pretty well right now, I must confess. If you’ve got the gaze as me, you’ll definitely name it some ethereal beauty like My Bloody Valentine Loveless, why not? And that’s the direction here. It is called browserless. My intentions here are not to start a revolution or reinvent the wheel.

Saturday morning, quick update here. The Telegram support is still only for Yolo detection models, however you can set it explicitly in the UI, not anymore inside the code, with your own user ID and Bot Token. And noooooooowwww the best news ever! It is right now deployed for distribution as an AppImage. That means, if you go to OpenQVision official GitHub ( https://github.com/dev-gazer/OpenQVision ), you’ll find in the dist folder an image anyone can run (sure, if you are a Linux user).

Hi all! There was a quick update in OpenQVision. I was talking to my friend Audrey Siqueira (https://github.com/audrey-siqueira) the other day and he suggested me to check whether it was possible to include object detection in images or videos, so expand OpenQVision scope beyond real time camera streaming. That change was pretty quick. Just one day after lauching v1.0.0, v1.1.0 is available. It is already merged to the main branch of OpenQVision official repository ( https://github.

Hi there and welcome! This is Alex here. I am starting this personal/semi-professional blog on GitHub. Let us then launch this space with a banger! Today I would like to present you a project I have been working hard these past couple of months. OpenQVision is a Open Source project that allows Computer Vision to become more readable by non-programmer users, or even helps data scientists to check their neural network models on the fly.