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OpenCV

OpenCV is the world's biggest computer vision library subtitle

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  • OpenCV Landing page
    Landing page //
    2023-07-29

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We have tracked the following product recommendations or mentions on various public social media platforms and blogs. They can help you see what people think about OpenCV and what they use it for.
  • Exploring Open-Source Alternatives to Landing AI for Robust MLOps
    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
  • Looking for a Windows auto-clicker with conditions
    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
  • Looking to recreate a cool AI assistant project with free tools
    - [ OpenCV](https://opencv.org/) instead of YoloV8 for computer vision and object detection. Source: 9 months ago
  • Looking to recreate a cool AI assistant project with free tools
    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: 9 months ago
  • What are the limits of blueprints?
    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: 11 months ago
  • Interesting problem trying to solve.
    Another option is using the OpenCV library with Python to extract features from images and compare them using feature matching algorithms like SIFT, SURF, or ORB. This approach is more computationally intensive but might be more accurate in identifying near-duplicates. You can find more information about OpenCV here: https://opencv.org/. Source: 12 months ago
  • A Guide to Blurring Images with OpenCV and Python
    If you're reading this, you're probably curious about computer vision, or just starting out. You've come to the right place. In this tutorial, we'll learn to blur images using OpenCV and Python. - Source: dev.to / about 1 year ago
  • How can I open an image, then iterate through the images pixels and check rgb value?
    Everything you describe can be done rather simply with opencv. Source: about 1 year ago
  • Managing your Azure Cognitive Search Costs
    If you find this cost prohibitive, you could try using some compute resources outside of Azure and a library like OpenCV or Azure Form Recognizer to try to extract meaning from image documents and then store the extracted information in Azure Cognitive Search instead of the source document. This typically is not worth the effort, however. - Source: dev.to / about 1 year ago
  • Real time images to Arduino Arrays conversion for use on LCD displays?
    To capture your eyes and make the determination of whether they are open or not (or to even copy the images to the LCD in realtime) will require a processor running much much faster than the average Arduino. Probably something making use of openCV (an extremely capable open source Computer Vision and image processing library). Arduino's (most) run at 16MHz. A Raspberry Pi or an ESP32 would be much more suited to... Source: about 1 year ago
  • Building a Deep learning model with Keras and ResNet-50
    You first import the OpenCV library. It will pre-process the selected flower image to ensure it has the same dimensions as the images that trained the deep learning model. - Source: dev.to / about 1 year ago
  • Does augmented reality websites work
    Hmm without the hardware support for AR-kit/Core, the camera has to do more of the heavy lifting. Not sure if there's a complete framework, but I know I heavily utilized https://opencv.org/ for camera based tracking for AR back in 2017 (before AR-kit/core were released). Source: over 1 year ago
  • Does there exist an API accessible from C# that detects faces in images?
    Alternatively, you can get into the nitty gritty of face detection yourself. OpenCV is a massive, open source project for all kinds computer vision tasks. Without jumping into the proprietary world, this is one of the most popular and capable computer vision libraries available. While powerful, OpenCV is comparatively low level; giving you the tools you need to accomplish your task, rather than a direct, single... Source: over 1 year ago
  • Camera array system for photogrammetry?
    OpenCV can do this for you, in fact it's probably better for the money and effort than solving your photogrammetry problem with hardware. I use it to create 3D images with two side-by-side GoPros. What you're looking for is the camera calibration process. Source: over 1 year ago
  • What is the smallest computer chip you can run a python program on?
    Many people use a Raspberry Pi single board computer (£10 - £50) and a cheap camera module as a security system. For example, I have one that uses OpenCV to tell me if someone or a vehicle I don't know is visiting (and different alerts for people or vehicles it recognises). Source: over 1 year ago
  • Truck caught up to me, quickly tail-gaited me, then passed and REVERSE HIGH-BEAMED. 🤣
    Yeah you can overlay images with geometric transformations to make them flat using software like OpenCV (https://opencv.org/), then upsample, but based on the video it would be unlikely that the frames have enough resolution to do so. Source: over 1 year ago
  • I’m not sure how to improve myself further
    By the way, my problem was much easier because it was on a track my car essentially had lanes to stay in. Yes, I stuck an iphone on thecar, and used the iphones camera to center the runner's face in the center of the screen using a library called OpenCV. I also used a rangefinder to determine distance from the car, and then you can basically triangulate with dynamics where the car needs to turn. There wasn't... Source: over 1 year ago
  • Hello friends. My 6th grader son is working on his science fair project, the teacher is getting married and she is not going to school for the next couple of weeks.
    You should be able to do this with opencv. https://opencv.org/. Source: over 1 year ago
  • App that measures consumption/cost of Analog Electric Meter
    If you need the precise values shown on the meter then you'll need to rig up a camera. You'll also need to space it far enough away that it can focus on the meter + have sufficient illumination. Take stills and then feed it into OpenCV. Something like https://github.com/mirogta/dial-meter-reader-opencv-py. Source: over 1 year ago
  • How To Make Vtuber Softwares?
    In terms of software, what you linked used optical tracking. The underlying tech is commonly called machine/computer vision. You can develop your own tracking software, but there's some open source solutions, like OpenCV than make it faster to build apps. (You can use OpenCV with Python bindings to learn the basics somewhat quickly). What you linked uses Kalidokit, an open source solution using TensorFlow.js and... Source: over 1 year ago
  • Which library/framework are standards for image processing?
    OpenCV (https://opencv.org/) was pretty standard last I was doing image processing in c/c++. Source: over 1 year ago

External sources with reviews and comparisons of OpenCV

7 Best Computer Vision Development Libraries in 2024
From the widespread adoption of OpenCV with its extensive algorithmic support to TensorFlow's role in machine learning-driven applications, these libraries play a vital role in real-world applications such as object detection, facial recognition, and image segmentation.
10 Python Libraries for Computer Vision
OpenCV is the go-to library for computer vision tasks. It boasts a vast collection of algorithms and functions that facilitate tasks such as image and video processing, feature extraction, object detection, and more. Its simple interface, extensive documentation, and compatibility with various platforms make it a preferred choice for both beginners and experts in the field.
Top 8 Alternatives to OpenCV for Computer Vision and Image Processing
OpenCV is an open-source computer vision and machine learning software library that was first released in 2000. It was initially developed by Intel, and now it is maintained by the OpenCV Foundation. OpenCV provides a set of tools and software development kits (SDKs) that help developers create computer vision applications. It is written in C++, but it supports several programming languages such as Python, Java,...
Top 8 Image-Processing Python Libraries Used in Machine Learning
These are some of the most basic operations that can be performed with the OpenCV on an image. Apart from this, OpenCV can perform operations such as Image Segmentation, Face Detection, Object Detection, 3-D reconstruction, feature extraction as well.
5 Ultimate Python Libraries for Image Processing
Pillow is an image processing library for Python derived from the PIL or the Python Imaging Library. Although it is not as powerful and fast as openCV it can be used for simple image manipulation works like cropping, resizing, rotating and greyscaling the image. Another benefit is that it can be used without NumPy and Matplotlib.
Top Python Libraries For Image Processing In 2021
To build computer vision and machine learning models, OpenCV has more than 2500+ algorithms. These algorithms are very much useful to perform various tasks such as face recognition, object detection, and many more. Let’s see some examples where we can perform using OpenCV:

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