cgoparam
gocv
cgoparam | gocv | |
---|---|---|
3 | 14 | |
15 | 6,307 | |
- | 1.6% | |
2.0 | 8.3 | |
about 1 year ago | 26 days ago | |
Go | Go | |
MIT License | GNU General Public License v3.0 or later |
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cgoparam
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Docs for the Go 1.20 experimental feature: arenas
I don't think it's out of the question- this experiment is very focused on the questions and concerns that were raised in the proposal, about how to handle arena memory and the concept of safety around it. If arenas settle on an MO that everyone feels comfortable with, there's a lot of possibilities for use cases to expand. That said, cgo arenas are already available via a library (self plug :]) - https://github.com/cannibalvox/cgoparam
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Is the opencv4 binding more efficient than python?
Serialization overhead. Python has serialization overhead that is rather substantial, in my understanding, and seems(?) to have a cost per-field or per-byte. Large data marshalling can be legitimately slow in python. By contrast, go has per-pointer serialization overhead. You can preallocate a scratch space in C and send pointers out of that and bring the serialization cost down to nearly zero. I do something similar with https://github.com/cannibalvox/cgoparam although it's intended for relatively small amounts of data, it could be a good starting point for something else.
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proposal: arena: new package providing memory arenas
So arenas are not intended to be thread-safe because they are not intended to last beyond the function where they are created. I have a cgo library that does memory arenas and I make it "thread safe" by putting the arenas themselves into a sync pool (so I can reuse memory pages) - https://github.com/cannibalvox/cgoparam
gocv
- Cylon: JavaScript framework for robotics, drones, and the Internet of Things
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GoCV 0.36 has just been released, no fooling
- Updated Docker images with OpenCV
https://github.com/hybridgroup/gocv/releases/tag/v0.36.0
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How can I install gocv?
- Installing from source gives me E: Unable to locate package libdc1394-22-dev
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Using GoCV to extract snapshots from IP-camera videostream
Can anyone guess if its possible to e.g. use - https://github.com/hybridgroup/gocv - permanently monitor the network stream via address e.g. http://192.169.178.20/action/stream?subject=mjpeg&user=user&pwd=secret - Generate/Extract a snapshot as image if configured items are detected e.g.: humans, cats, cars, dogs
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Can I build projects in Go without knowing front-end/client development?
But if you want to have something to show: I've played around with https://gocv.io/ and was quite impressed what this library can do with the video input from your camera input.
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Is the opencv4 binding more efficient than python?
I have just found the gocv package. I have a video analyzer program written in python, however im thinking about rewriting on golang for optimizing the execution time. Its a good idea or its better to just use the phyton one.
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Image manipulation with Go
https://github.com/hybridgroup/gocv has openCV bindings.
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GoCV on the yolo Darknet model
I am working on a custom model, I have been through this example to apply it on my use case but the output I get has random detection from perform detection, how do I work with gocv.Mat structure and is there any example with yolo darknet model? Any help is appreciated if you can direct me to right resources where I can better understand how the output mat is to be parsed to get the box! Thanks in advance!
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Anyone interested in helping me build a object detection with Tensorflow + Golang
I think https://github.com/hybridgroup/gocv accepts tensorflow model format, why not use that?
- Recommendations for building a reverse image search engine
What are some alternatives?
go - The Go programming language
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
resize - Pure golang image resizing
go-opencv - Go bindings for OpenCV / 2.x API in gocv / 1.x API in opencv
pigo - Fast face detection, pupil/eyes localization and facial landmark points detection library in pure Go.
imaging - Imaging is a simple image processing package for Go
smartcrop - smartcrop finds good image crops for arbitrary crop sizes
imaginary - Fast, simple, scalable, Docker-ready HTTP microservice for high-level image processing
bimg - Go package for fast high-level image processing powered by libvips C library
goimagehash - Go Perceptual image hashing package
govips - A lightning fast image processing and resizing library for Go
Primitive Pictures - Reproducing images with geometric primitives.