imagick
OpenCV
imagick | OpenCV | |
---|---|---|
3 | 215 | |
1,817 | 82,293 | |
0.5% | 1.1% | |
3.6 | 9.9 | |
5 months ago | 3 days ago | |
Go | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
imagick
-
Golang library similar to Python's pillow
If you want my opinion on which one to use, I would recommend this one, as there exist bindings for a huge amount of languages.
-
Best way to composite millions of tiny 16x16 images together?
Looks like the kind of problem I'd solve with imagick https://github.com/gographics/imagick
- How to call C++ (wrapped with python) in Go
OpenCV
-
How to Fix Go Project Build Error with gocv on Android?
git clone https://github.com/opencv/opencv.git cd opencv git checkout 4.x
-
Grasping Computer Vision Fundamentals Using Python
To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but contextualise them with human-like reasoning. Start building, and you’ll shape how tomorrow’s machines perceive reality.
-
Top Programming Languages for AI Development in 2025
Ideal For: Computer vision, NLP, deep learning, and machine learning
- AI ตรวจจับใบหน้าด้วย OpenCV แบบเรียลไทม์: เริ่มต้นง่าย ๆ ด้วย Python
- Accelerating OpenCV with CUDA on Jetson Orin NX: A Complete Build Guide
-
How to draw an outline in a video game
Note that the 'Jump Flood Algorithm' is O(N log N) where N is the number of pixels. There is a better O(N) algorithm which can be parallelized over the number of rows/columns of an image:
https://news.ycombinator.com/item?id=36809404
Unfortunately, it requires random access writes (compute shaders) if you want to run it on the GPU. But if CPU is fine, here are a few implementations:
JavaScript: https://parmanoir.com/distance/
C: https://github.com/983/df
C++: https://github.com/opencv/opencv/blob/4.x/modules/imgproc/sr...
Python: https://github.com/pymatting/pymatting/blob/afd2dec073cb08b8...
-
20 Open Source Tools I Recommend to Build, Share, and Run AI Projects
OpenCV is an open-source computer vision and machine learning software library that allows users to perform various ML tasks, from processing images and videos to identifying objects, faces, or handwriting. Besides object detection, this platform can also be used for complex computer vision tasks like Geometry-based monocular or stereo computer vision.
-
F1 FollowLine + HSV filter + PID Controller
This library is used for image and video processing, offering functions for tasks like object detection, filtering, and transformations in computer vision.
-
Smile Detector and Photo Capture
Download the Haar cascade XML files for face and smile detection: https://github.com/opencv/opencv/tree/master/data/haarcascades
-
Install OpenCV 4.5 on Ubuntu 22.04
Let's open the most recent release of opencv to the date of this video capturing: https://github.com/opencv/opencv/releases/tag/4.5.1
What are some alternatives?
libvips - A fast image processing library with low memory needs.
OpenImageIO - Reading, writing, and processing images in a wide variety of file formats, using a format-agnostic API, aimed at VFX applications.
CImg - The CImg Library is a small and open-source C++ toolkit for image processing
imaginary - Fast, simple, scalable, Docker-ready HTTP microservice for high-level image processing
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.