fastAPI_TDD_Docker
ffvideo
fastAPI_TDD_Docker | ffvideo | |
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4 | 22 | |
8 | 39 | |
- | - | |
2.8 | 0.0 | |
about 1 year ago | over 2 years ago | |
JavaScript | C++ | |
The Unlicense | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
fastAPI_TDD_Docker
- What would you love to learn in an intermediate / advanced FastAPI book?
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SSL: CERTIFICATE_VERIFY_FAILED
Here's a Github containerized FastAPI project of mine with the Traefik integration already in place: https://github.com/bsenftner/fastAPI_TDD_Docker (note: I have a notice on that page informing readers there is newer work at another repo of mine - that one does not have the Traefik integration in place yet.
- Ways to create GUI for computer vision software
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Dockerfile for FastAPI app without security vulnerabilities?
My project is public here: https://github.com/bsenftner/fastAPI_TDD_Docker
ffvideo
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Ask HN: What apps have you created for your own use?
I wrote an optimized C++ FFMPEG player as a video surveillance system, initially to watch my pets in my yard, and then kept going adding (human) face detection, and then a DL/ML training scaffold, then Live555 re-encoding, then an embedded web browser, then I added tons of comments and turned it into a learning demo project. It's on Github, I still use it to watch my pets: https://github.com/bsenftner/ffvideo
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Looking for a VMS and some doubts
Are your camera's ONVIF compatible? You can confirm this by running this free open source software: https://sourceforge.net/projects/onvifdm/ If your cameras appear in this software, then they are ONVIF compatible. If they are, then you can use my free and open source windows video player to view as many stream as you want: https://github.com/bsenftner/ffvideo This player is CPU efficient, intended for use when training video based machine learning models, so it leaves processor available for machine training. Used as a pure video player, I've had 32 video windows playing at 30 fps simultaneously using it on an i9 3.2 Ghz workstation.
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[Question] I'm running facial recognition code however the video and the detection is extremely slow. Is there a way to reduce the lag of the video
In my ffmpeg playback library, be aware it is optimized for computer vision; therefore any audio is ignored and if playing from a file any timing information is ignored as well. When playing real time streams, such as from an IP camera or USB camera that playback is as close to real time as possible. I seem to remember something like under 20 ms per frame latency. However, IP video services expect timing information to be honored, and because mine ignores timing a YouTube video will fly by a few hundred frames per second. Likewise, playing from a local stored video file will playback as fast as your drive delivers frames. It was designed this way to minimize overhead and delay when training algorithms with video. Here's the essential source to the playback lib: https://github.com/bsenftner/ffvideo/tree/master/ffvideolib_src
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Anyone have experience using modern OpenGL w/ wxWidgets?
Okay, thanks to u/bsenftner I was able to figure this out by looking at his Github repository. Essentially, if you want to use a specific version of OpenGL with wxGLCanvas you have to specify the major and minor versions in the attribute list passed to the constructor of wxGLCanvas.
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Parallel programming for computer vision applications
If you take a look at my ffvideo github project (linked in my reply above) you can search for instances of std::thread and see they are fairly self contained, with logical data fencing protecting data shared between threads. Here's an example: a video frame exporter that runs in it's own thread, enabled when the end-user wants video frames written to disk: https://github.com/bsenftner/ffvideo/blob/aed42b5a3e856e24b030e71f6d92bcbabf5d6829/ffvideolib_src/ffvideo_frameExporter.h
- USB camera feed lagging when used with openCV
- Ways to create GUI for computer vision software
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RTSP program
Try this: https://github.com/bsenftner/ffvideo
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Video + bounding box coupled stream transmission
I do this in C++ here: https://github.com/bsenftner/ffvideo I think I'm using DLib rather than OpenCV, but at this level the difference between the two is negligible.
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Doable? Cropping and alignment of photo set based on facial landmarks
I have some code doing this in an open source C++ project here: https://github.com/bsenftner/ffvideo Towards the bottom of the README on that page you'll see an image titled "demonstrating tilted head registration" describing what you're trying to do here.
What are some alternatives?
make-fastapi-app - Creates a FastAPI App
nicegui - Create web-based user interfaces with Python. The nice way.
jwt-tutorial - How to secure sensitive endpoints using JWT in Node.js
msdfgen - Multi-channel signed distance field generator
miniCMS - A document and content managment system for small businesses
Dlib - A toolkit for making real world machine learning and data analysis applications in C++
ffmpeg_shadertoy_filter
CV-camera-finder - A simple function to find devices on windows using media foundation
dlib-android - :dragon: Port dlib to Android
displaycameras - System for displaying RTSP feeds from IP cameras on the Raspberry Pi
Side-Profile-Detection - Detecting face profiles (i.e., frontal, left, and right) using face detection model MTCNN