G'MIC VS OpenCV
Compare G'MIC VS OpenCV and see what are their differences
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives.
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G'MIC
ImageMagick
GraphicsMagick
GIMP
Adobe Photoshop
Inkscape
GenFavicon
FFmpeg
OpenCV
Scikit-learn
Pandas
NumPy
Dataiku
Exploratory
htm.java
WEKA
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OpenCV might be a bit more popular than G'MIC. We know about 50 links to it since March 2021 and only 34 links to G'MIC. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
But I would use G'MIC as you can scale the grain, control opacity Filters > G'MIC_Qt, a window opens Degradations > Add Grain > https://i.imgur.com/FHXJ6CF.jpg. Source: 5 months ago
G'MIC will do it, On the GIMP top menu go to Filters > G'MIC_Qt, do your color correction and then at the bottom on the input select "All" or "All visible" or whatnot (multiple option). Source: 11 months ago
This is just GMIC filters which are an awesome free filter suite for Photoshop/Gimp/Krita. Source: 12 months ago
You do not need to abandon the ship, with 2 plugins (one is G'MIC, the other one is to export layers as image and it does way more as well), and a one line code in terminal, you will be able to do it with GIMP (although I think it's the perfect job for ImageMagick, but I don't master it). Source: about 1 year ago
With a plugin, GMIC you can also produce the average layer, so that spares you setting all the opacities. You still have to load them in Gimp (not too likely to have hem all fit and display). You can also use GMIC directly in a command line (but again, a command line with 75000 files is not obvious, so you may also have to divide and conquer). Source: about 1 year ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/). Source: 5 months ago
- [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 10 months ago
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... Source: 10 months ago
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++. Source: 12 months ago
ImageMagick - ImageMagick is a software suite to create, edit, and compose bitmap images.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
GraphicsMagick - GraphicsMagick is the swiss army knife of image processing.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
GIMP - GIMP is a multiplatform photo manipulation tool.
NumPy - NumPy is the fundamental package for scientific computing with Python