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 / 8 days ago
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: Reddit / about 2 months ago
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 2 months ago
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: Reddit / 3 months ago
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: Reddit / 3 months ago
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: Reddit / 3 months ago
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: Reddit / 3 months ago
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: Reddit / 4 months ago
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: Reddit / 4 months ago
You should be able to do this with opencv. https://opencv.org/. - Source: Reddit / 4 months ago
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: Reddit / 6 months ago
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: Reddit / 6 months ago
OpenCV (https://opencv.org/) was pretty standard last I was doing image processing in c/c++. - Source: Reddit / 6 months ago
Basically, take two (or more) high performance cameras spaced some known distance apart (distance depends on how far you expect the object to track will be from the cameras) and film the same object in the sky. If the optical parameters, location, and orientation of both cameras are known, you can use algorithms from image processing libraries (i.e. OpenCV) to determine the tracked object's location, speed, and size. - Source: Reddit / 6 months ago
The post examines the implementation of Identity and Access Management (IAM) in the Computer Vision Annotation Tool (CVAT), which is a part of the OpenCV ecosystem. CVAT helps to annotate raw images and video files to produce a ready-to-use Computer Vision dataset in popular formats such as MS COCO, PASCAL VOC, YOLO, etc. Here we will cover:. - Source: Reddit / 6 months ago
Try out OpenCV and Kaggle for basics on image manipulation and data science: https://opencv.org/ and https://www.kaggle.com/. - Source: Reddit / 7 months ago
I think you should just use its dependency OpenCV directly. I would also start with this Sudoku solver that uses OpenCV: https://pyimagesearch.com/2020/08/10/opencv-sudoku-solver-and-ocr/. - Source: Reddit / 7 months ago
This could be done with OpenCV. Actually, someone already made something like that. - Source: Reddit / 9 months ago
So... I downloaded the client tonight and out of curiosity I browsed the installation folder. There I found out a lot of files that enable recognition through computer vision. Namely, there is a full OpenCV implementation as well as a few files that refer to Face Detection and Face Analysis. - Source: Reddit / 10 months ago
OpenCV stereo block matching and semi-global block matching baselines, with all their parameters. - Source: Reddit / 10 months ago
If you are into Computer vision, you probably are familiar with OpenCV. Its an amazing library that has almost everything one needs to do 2D and 3D processing and much more. Gesture recognition, face detection, Motion tracking, think of anything related to image processing and OpenCV can be your goto. Its based on the BSD license, so you can just download it and start using it. - Source: dev.to / 11 months ago
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