Search Results for "omr python opencv"
Sort By:
Showing 27 open source projects for "omr python opencv"
View related business solutions-
Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
-
HubSpot is an AI-powered customer platform with all the software, integrations, and resources you need to connect your marketing, sales, and customer service. HubSpot's connected platform enables you to grow your business faster by focusing on what matters most: your customers.
-
1
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! https://docs.opencv.org/master... -
2
Frigate
NVR with realtime local object detection for IP cameras
Frigate - NVR With Realtime Object Detection for IP Cameras A complete and local NVR designed for Home Assistant with AI object detection. Uses OpenCV and Tensorflow to perform realtime object detection locally for IP cameras. Use of a Google Coral Accelerator is optional, but highly recommended. The Coral will outperform even the best CPUs and can process 100+ FPS with very little overhead. -
3
OpenFace Face Recognition
Face recognition with deep neural networks
OpenFace is a Python and Torch implementation of face recognition with deep neural networks and is based on the CVPR 2015 paper FaceNet: A Unified Embedding for Face Recognition and Clustering by Florian Schroff, Dmitry Kalenichenko, and James Philbin at Google. Torch allows the network to be executed on a CPU or with CUDA. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google... -
4
Synapse Machine Learning
Simple and distributed Machine Learning
..., and OpenCV. These tools enable powerful and highly-scalable predictive and analytical models for a variety of data sources. SynapseML also brings new networking capabilities to the Spark Ecosystem. With the HTTP on Spark project, users can embed any web service into their SparkML models. For production-grade deployment, the Spark Serving project enables high throughput, sub-millisecond latency web services, backed by your Spark cluster. -
KrakenD is a high-performance API Gateway optimized for resource efficiency, capable of managing 70,000 requests per second on a single instance. The stateless architecture allows for straightforward, linear scalability, eliminating the need for complex coordination or database maintenance.
-
5
[OFFICIAL] tinyfiledialogs v3.18.2 C C++
inputbox password WIN OSX GTK QT Console VCPKG C# Lua R Fortran Pascal
* OFFICIAL WEBSITE * v3.18.2 one C/C++ file & header provides 8 functions: - beep - tray notify popup - message & question - input & password - save file - open file(s) - select folder - color picker complements OpenGL Vulkan GLFW GLUT GLUI VTK SFML TGUI SDL Ogre Unity3d ION OpenCV CeGui MathGL GLM CPW GLOW Open3D ImGui MyGui GLT NGL STB Nuklear Fenster MicroUi & GUI-less programs NO INIT NO MAIN LOOP NO LINKING NO INCLUDE win (XP to 11) ASCII MBCS UTF-8 UTF-16 (wchar_t... -
6
Face Mask Detection
Face Mask Detection system based on computer vision and deep learning
Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential districts... -
7
Easy Upscale
A simple image upscaler application using EDSR, ESPCN, FSRCNN, etc.
This application was made to fulfill the assignment for the Data Structures course. The concept of the application is an application to upgrade/enhance image quality. The main theme is queues, we implement circular queues for pooling/storing a list of images to be upscaled. Gui creation is made manually using the tkinter library. For the upscale process itself, it uses the OpenCV library with a model obtained from open source. Checked using vermin. Minimum required versions: 3.6 Incompatible... -
8
qiji-font
Typeface from Ming Dynasty woodblock printed books
... replaceable by an automatic corner-detection algorithm). Generate a low-poly mask for each character on the grid, and save the thumbnails (using OpenCV). First, red channel is subtracted from the grayscale, in order to clean the annotations printed in red ink. Next, the image is thresholded and fed into the contour-tracing algorithm. A metric is then used to discard shapes that are unlikely to be part of the character in interest. -
9
Upscale
This program is upscaling any image by a factor 2 using an algorithm
This program is upscaling any image by a factor 2 using an algorithm of cubic interpolation. You may need to install the following libraries to run the program, tqdm, itertools, and OpenCV. -
Google Cloud’s AI-powered APIs help you translate documents, websites, apps, audio files, videos, and more at scale with best-in-class quality and enterprise-grade control and security.
-
10
Semantic Segmentation in PyTorch
Semantic segmentation models, datasets & losses implemented in PyTorch
Semantic segmentation models, datasets and losses implemented in PyTorch. PyTorch and Torchvision needs to be installed before running the scripts, together with PIL and opencv for data-preprocessing and tqdm for showing the training progress. PyTorch v1.1 is supported (using the new supported tensoboard); can work with earlier versions, but instead of using tensoboard, use tensoboardX. Poly learning rate, where the learning rate is scaled down linearly from the starting value down to zero... -
11
3DDFA
Fast, accurate and stable 3D dense face alignment
...++ and cython is also included. This repo supports the onnxruntime, and the latency of regressing 3DMM parameters using the default backbone is about 1.35ms/image on CPU with a single image as input. See requirements.txt, tested on macOS and Linux platforms. The Windows users may refer to FQA for building issues. Note that this repo uses Python3. The major dependencies are PyTorch, numpy, opencv-python and onnxruntime, etc. -
12
cv2_plt_imshow
Using matplotlib_imshow for images read by cv2
... of contents * [Setup](#setup) * [Dependencies](#dependencies) * [Contact](#contact) ## Setup ```pip install cv2_plt_imshow``` ## Dependencies * [matplotlib](https://pypi.org/project/matplotlib/) * [cv2](https://pypi.org/project/opencv-python/) ## Contact * [Author](https://rupesh.info/) * [Github](https://github.com/rs9899/cv2_plt_imshow) -
13
DCVGAN
DCVGAN: Depth Conditional Video Generation, ICIP 2019.
This paper proposes a new GAN architecture for video generation with depth videos and color videos. The proposed model explicitly uses the information of depth in a video sequence as additional information for a GAN-based video generation scheme to make the model understands scene dynamics more accurately. The model uses pairs of color video and depth video for training and generates a video using the two steps. Generate the depth video to model the scene dynamics based on the geometrical... -
14
Rainbow
Rainbow: Combining Improvements in Deep Reinforcement Learning
Combining improvements in deep reinforcement learning. Results and pretrained models can be found in the releases. Data-efficient Rainbow can be run using several options (note that the "unbounded" memory is implemented here in practice by manually setting the memory capacity to be the same as the maximum number of timesteps). -
15
Micrometer CNC 4 Raspberry Pi3
A debian image with linux RT kernel, OpenCV345, ROS, and LinuxCNC
This OS is a configured version of Raspbian (debian OS) that focuses on 3D printing, CNC controllers, and CAD/CAM applications. It includes many tweaks to get the GPU acceleration on webGL, VLC and Flash video for example. Since rc2, we now use F2FS for /home to improve sdcard performance. It was load tested on the pi2, pi3, and Pi3B+. It is based on a stripped down MATE desktop, and is intended to be shared along with the documented hardware projects. Please use the GPG key posted on the... -
16
Face Recognition
World's simplest facial recognition api for Python & the command line
Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition... -
17
Machine Learning for OpenCV
M. Beyeler (2017). Machine Learning for OpenCV
M. Beyeler (2017). Machine Learning for OpenCV: Intelligent image processing with Python. Packt Publishing Ltd., ISBN 978-178398028-4. -
18
Raspbian w/OpenCV & SimpleCV
Raspbian w/OpenCV & SimpleCV
After wasting several hours following multiple tutorials attempting to install OpenCV and SimpleCV on a fresh Raspbian image only to end up with a combination of packages that were outdated or otherwise non-functional, once I found a working setup, I made this image to have a good point to go back to save time reinstalling all the dependencies. This is Raspbian Jessie (full) with Python OpenCV installed via apt-get and SimpleCV installed via pip -
19
OhodO
OhodO optical marks recogination
OhodO is optical marks recogination, written by python 3.6, opencv 3, tkinter. work with webcam of the laptop or usb webcam. -
20
Eye Connect
The first free cross-platform HCI for upper body paralysis.
... designed to provide full system control through facial feature detections. Watch the video: https://www.youtube.com/watch?v=LowRaG3dflA Requirements: - A Linux, Windows or Mac environment. - A Python 2.0 Installation - A webcam - the OpenCV library - The pyuserinput library -
21
visual debugger
image visual debugger
Visualize the in-memory images when you are debugging an OpenCV C/C++ program. It uses the GDB's Python interface, and works in multiply platforms. -
22
PyVision Computer Vision Toolkit
A Python computer vision library
PyVision is a object-oriented Computer Vision Toolkit for researchers that contains vision and machine learning algorithms and algorithm analysis and easily interfaces with scipy/numpy, PIL, opencv and other computer and machine learning libraries. -
23
jayso-opencv
Ubuntu 12.04.2 LTS ISO file with OpenCV 2.4.2
Ubuntu 12.04.2 LTS ISO file with OpenCV 2.4.2 configured and installed along with python support. In a nutshell, grab this ISO file and do the normal Ubuntu installation(or use it in live mode) and upon completion, you will have the OpenCV 2.4.2 library ready to use. Please refer the wiki for more information. -
24
pyShotDetect
(Auto-)Detect Video Scene Changes, output an edit list
Update Node: R3 incorporates a variety of UI improvements and standard timecode export. Given a .dv file automatically detect scene changes within that file (best performance on cuts and fade through/to black). Write a .kino file with each of the scenes for post-processing. Dependencies: (Python) openCV matplotlib Tkinter -
25
PROYECTO DE GRADO PARA LA OBTENCIÓN DEL TÍTULO DE INGENIERÍA MAPAS DE ENTORNOS MEDIANTE NAVEGACIÓN DIFUSA Y UN SISTEMA DE TELEOPERACIÓN DE UNA PLATAFORMA PIONNER P3-DX Realizar un mapeo basico y un control difuso de velocidad para la plataforma Pionner P3-DX Requierimientos: -Aria y ArNetworking -Python 2.5 - 2.7 -pyGTK -openCV -pyfuzzy