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Showing 16 open source projects for "real"
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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AWS IoT FleetWise Edge
AWS IoT FleetWise Edge Agent
Easily collect, transform, and transfer vehicle data to the cloud in near-real-time. AWS IoT FleetWise makes it easy and cost-effective for automakers to collect, transform, and transfer vehicle data to the cloud in near-real-time and use it to build applications with analytics and machine learning that improve vehicle quality, safety, and autonomy. Train autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) with camera data collected from a fleet of production vehicles. ... -
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OpenCV
Open Source Computer Vision Library
The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials! -
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AirSim
A simulator for drones, cars and more, built on Unreal Engine
AirSim is an open-source, cross platform simulator for drones, cars and more vehicles, built on Unreal Engine with an experimental Unity release in the works. It supports software-in-the-loop simulation with popular flight controllers such as PX4 & ArduPilot and hardware-in-loop with PX4 for physically and visually realistic simulations. It is developed as an Unreal plugin that can simply be dropped into any Unreal environment. AirSim's development is oriented towards the goal of creating a... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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YOLO ROS
YOLO ROS: Real-Time Object Detection for ROS
This is a ROS package developed for object detection in camera images. You only look once (YOLO) is a state-of-the-art, real-time object detection system. In the following ROS package, you are able to use YOLO (V3) on GPU and CPU. The pre-trained model of the convolutional neural network is able to detect pre-trained classes including the data set from VOC and COCO, or you can also create a network with your own detection objects. The YOLO packages have been tested under ROS Noetic and Ubuntu 20.04. ... -
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OpenPose
Real-time multi-person keypoint detection library for body, face, etc.
OpenPose has represented the first real-time multi-person system to jointly detect human body, hand, facial, and foot keypoints (in total 135 keypoints) on single images. It is authored by Ginés Hidalgo, Zhe Cao, Tomas Simon, Shih-En Wei, Yaadhav Raaj, Hanbyul Joo, and Yaser Sheikh. It is maintained by Ginés Hidalgo and Yaadhav Raaj. OpenPose would not be possible without the CMU Panoptic Studio dataset. -
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opencv4nodejs
Nodejs bindings to OpenCV 3 and OpenCV 4
OpenCV4NodeJS is a Node.js binding for OpenCV, allowing developers to integrate computer vision capabilities directly into JavaScript applications for image processing, object detection, and facial recognition. -
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node-opencv
OpenCV Bindings for node.js
OpenCV bindings for Node.js. OpenCV is the defacto computer vision library - by interfacing with it natively in node, we get powerful real time vision in js. People are using node-opencv to fly control quadrocoptors, detect faces from webcam images and annotate video streams. If you're using it for something cool, I'd love to hear about it! You'll need OpenCV 2.3.1 or newer installed before installing node-opencv. You can use opencv to read in image files. Supported formats are in the OpenCV docs, but jpgs etc are supported. ... -
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LBP in multiple platforms
LBP implementation in multiple computing platforms (ARM,GPU, DSP...)
...This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. "Evaluation of real-time LBP computing in multiple architectures," Journal of Real Time Image Processing, 2014 -
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EStereo is a computer vision C++ library for real-time disparity estimation. It computes dense stereo matching from 2 or 3 images as well as 3D scene reconstruction. The library also comes with a GUI-based application (StereoPlus).
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Solving problems of counting the number of vehicles passing on a road during an interval time, as well as the problems of vehicles classification and estimating the speed of the observed traffic flow from traffic scenes acquired by a camera in real-time.
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A system for playing chess with a computer player using a real chess board. An experiment in learning the techniques of Computer Vision and having fun in the process.
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The Mimas Toolkit is a C++ real-time computer vision library. Algorithms include edge/corner-detection, object recognition/tracking, LSI-filters, segmentation, array-operators, convolution etc. OO wrappers for LAPACK, libxine, V4L, FFTW are provided.
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The goal of cvtk is to provide an easy to use computer vision framework that allows real-time tracking of color-marked objects in 2 dimensions.
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Smart eye is a C++ API for computer vision that aim to provide real-time ET technology communicating with computer HCI systems.
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Savant
Python Computer Vision & Video Analytics Framework With Batteries Incl
Savant is an open-source, high-level framework for building real-time, streaming, highly efficient multimedia AI applications on the Nvidia stack. It helps to develop dynamic, fault-tolerant inference pipelines that utilize the best Nvidia approaches for data center and edge accelerators. Savant is built on DeepStream and provides a high-level abstraction layer for building inference pipelines.
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