OpenCV VS libvips

- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection

I came across a very interesting [project]( (4) Mckay Wrigley on Twitter: "My goal is to (hopefully!) add my house to the dataset over time so that I have an indoor assistant with knowledge of my surroundings. It’s basically just a slow process of building a good enough dataset. I hacked this together for 2 reasons: 1) It was fun, and I wanted to…" / X ) made by Mckay Wrigley and I was wondering what's the easiest way to implement it using free, open-source software. Here's what he used originally, followed by some open source candidates I'm considering but would love feedback and advice before starting: Original Tools: - YoloV8 does the heavy lifting with the object detection - OpenAI Whisper handles voice - GPT-4 handles the “AI” - Google Custom Search Engine handles web browsing - MacOS/iOS handles streaming the video from my iPhone to my Mac - Python for the rest Open Source Alternatives: - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection - Replacing GPT-4 is still a challenge as I know there are some good open-source LLms like Llama 2, but I don't know how to apply this in the code perhaps in the form of api - [DeepSpeech](https://github.com/mozilla/DeepSpeech) rather than Whisper for offline speech-to-text - [Coqui TTS](https://github.com/coqui-ai/TTS) instead of Whisper for text-to-speech - Browser automation with [Selenium](https://www.selenium.dev/) instead of Google Custom Search - Stream video from phone via RTSP instead of iOS integration - Python for rest of code I'm new to working with tools like OpenCV, DeepSpeech, etc so would love any advice on the best way to replicate the original project in an open source way before I dive in. Are there any good guides or better resources out there? What are some pitfalls to avoid? Any help is much appreciated!

Glancing at the code, I think it's detectMultiScaleNoGrouping and then the operator() of CascadeClassifierInvoker gets called. It will probably help you to put a breakpoint and step through that bit of the code.

On GitHub https://github.com/opencv/opencv

OpenCV

You also need C++ if you're going to do things which aren't built in as part of the engine. As an example if you're looking at using compute shaders, inbuilt native APIs such as a mobile phone's location services, or a third-party library such as OpenCV, then you're going to need C++.

wget -O opencv.zip https://github.com/opencv/opencv/archive/4.1.0.zip

Sharp is a fast and efficient image optimization Node.js module that makes use of the native libvips library.

h2non/bimg can handle both if the underlying libvips is compiled with support for both formats.

if you're using linux (which it doesn't seem so) there's also vispdisp https://github.com/jcupitt/vipsdisp which is based on https://github.com/libvips/libvips which will likely take over how images are decoded in the future for everything, at least methodology wise.

The magic happens by way of a library called Libvips, which contains an ultra-high-speed low-memory image resizer.

imagor uses one of the most efficient image processing library libvips. It is typically 4-8x faster than using the quickest ImageMagick and GraphicsMagick settings.

libvips v8.6+ or ImageMagick for image analysis and transformations

- [libvips](https://github.com/libvips/libvips)

That's very cool! Though performance will not be close -- your nice solution is based on libgd, which is typically 5x slower than libvips, and needs 10x more memory. At usual display sizes, libvips will generally deliver the resized image in under 50ms, and will handle large images (relatively) gracefully.

https://github.com/libvips/libvips https://github.com/libvips/libvips/wiki/Why-is-libvips-quick interesting

As mentioned, active storage uses third-party software to enable file processing. You can download and install libvipsor ImageMagick v8.6+ for image analysis and transformations, ffmpeg v3.4+ for video/audio analysis and video previews, and poppleror muPDFfor PDF previews separately, as Rails will not install this software.