Image Recognition Project Github

However the theories they use are similar but the techniques and approaches are different. pdf / supplementary / project page / code (github) / poster. Provides you a simple DOM API to do voice recognition (speech to text). In this post, we're going to dab a little bit in machine learning and face recognition to predict if an image from a live webcam shows a smiling subject or not. Image recognition goes much further, however. As always, I hope this project can help others find their way into the exciting world of electronics! For details and final code, please visit my GitHub depository: OpenCV-Face-Recognition. This page highlights a few of the open source projects created and released by our engineers. COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. We haven't opened it on GitHub yet, but our SLAMBench suite, providing multi-platform, multi-language implementations of KinectFusion and soon other state-of-the-art SLAM algorithms might be of interest. Download Project – Currency Recognition System using Image Processing >> 100+ Projects on Image Processing. Theme based on BlackTie. Bonus points in the answer if you would replace the image with text for copy/paste. just for your project. We had started out with just a faint hope that at least we will learn something and most probably we will not be able to come up with anything close to a finished code. 301 Moved Permanently. Google Images. Open source software is an important piece of the data science puzzle. In recent years, deep learning has enabled huge progress in many domains including computer vision, speech, NLP, and robotics. my research projects and demos. Image Recognition. I want to preprocess image for tesseract, and I'm stuck on detection of license plate (rectangle detection). If you want to contribute to the project, this part of the documentation is for you. The easiest way to use sphinx4 is to use modern build tools like Apache Maven or Gradle. Decision Tree Classifier A machine learning classifier of the best sort. ToothNet: Automatic Tooth Instance Segmentation and Identification from Cone Beam CT Images Zhiming Cui, Changjian Li, Wenping Wang. IIIT Allahabad's month long open-source competition. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. Tags: medical image, image recognition, deep learning, convolutional neural networks, cnn, CNTK, image classification, lung cancer detection, boosted decision trees, LightGBM, kaggle, competition, data science bowl. All gists Back to GitHub. Or if you want to distribute your application with an image recognition database through the application Store? So in this little tutorial, I show you some simple trick to package your object recognition in your app. See our arXiv report for details on our approach. The word “biometrics” is also used to denote biometric recognition methods. It is a javascript version of the Tesseract Open Source OCR Engine. I am focusing on the development and maintenance of scikit-learn which is a machine-learning Python package. Commercial quality OCR. >14 million pictures organized in >20k categories. This project is maintained by Christoph Oberhofer. Icons from Noun Project. Authors: Yaojia Wang | Siyuan Lin. Repo for a small image recognition project in python. A Project status badge is a dynamically generated image displaying the status of the last build. What is this? This is a developer demo of the Adobe Creative SDK Image Editor for Web. This week, Google introduced a new kit for your project based on the Raspberry Pi Zero W board. Machine learning algorithm [Convolutional Neural Networks] is used to classify the image. This week we are going to talk about image recognition in augmented reality. This repository contains a collection of many datasets used for various Optical Music Recognition tasks, including staff-line detection and removal, training of Convolutional Neuronal Networks (CNNs) or validating existing systems by comparing your system with a known ground-truth. Li Shen (申丽) lshen. GitHub project link: TF Image Classifier with python. To perform this you need to just edit the " — image_file" argument like this. InnerEye is a research project that uses state of the art machine learning technology to build innovative tools for the automatic, quantitative analysis of three-dimensional radiological images. The data used for the study can be found here. COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. it is a method to help computers recognize different textures or characters. So I tried GitHub Community. It is a simple OCR (Optical Character Recognition) program that can convert scanned images of text back into text. The uSpeech library provides an interface for voice recognition using the Arduino. Image recognition and face detection has been around for some years. The field of biometrics examines the unique physical or behavioral traits that can be used to determine a person’s identity. Action Recognition using Visual Attention [ arXiv | PDF Available on GitHub The above images show the attention of our model over time for a few examples from. GitHub for Find-Object; I posted a video on my another project RTAB-Map where Find-Object runs in parallel during the mapping (you can try the demo here). Content-based Image Recognition (CBIR) A project for Multimedia Processing. I have executed the "tess-two-test" project by importing the three project files but "tess-two-test" does not include any activities so it will not run. each image in CIFAR-10 is a point in 3072-dimensional space of 32x32x3 pixels). The next step is to train corresponding 2 images as a good model input, and get 2 160-bit dimensional feature vector. Here are a few to consider. Use object detection to let your cat in and out of the house with a motion-activated pet door. Conservative Republicans like. Images can be thought of as two-dimensional signals via a matrix representation, and image processing can be understood… Currency Recognition System using Image Processing It is difficult for people to recognize currencies from different. The software first captures an image of all the authorized persons and stores the information into database. Installation & Configuration. computer server dedicated to AI to the Open Compute Project — a group consisting. In recent years, deep learning has enabled huge progress in many domains including computer vision, speech, NLP, and robotics. Tesseract is a tool that recognizes the text in images using Optical Character Recognition (OCR). Attribute Classifiers v2 Released Per image, attributes now classified in ~12sec. Joerg Schulenburg started the program, and now leads a team of developers. Commercial quality OCR. You can perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration, and 3D image processing. While GitHub has name recognition as a web-based version control and developer tool, teams should evaluate any of several viable GitHub alternatives for projects. TWRP Builder is a project that aims at creating Team Win Recovery Project (TWRP) for the devices which don't have their own TWRP support yet. "- Put more images of each person (under different lighting conditions, taken on different days, etc. Theme based on BlackTie. DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. Open source project which allows to mix Appium and Sikuli under one framework and easy manipulate by content and recognition of images. In a nutshell, a face recognition system extracts features from an input face image and compares them to the features of labeled faces in a database. I am presently working on a Augmented Reality project using Vuforia that uses Speech recognition to control the objects in Unity. https://github. I sure want to tell that BOVW is one of the finest things I’ve encountered in my vision explorations until now. PocketSphinx Android demo a project from VCS. See our arXiv report for details on our approach. Apple's ARKit 1. GitHub makes it easy to add one at the same time you create your new repository. Our network architecture for face recognition is based on ResNet-34 from the Deep Residual Learning for Image Recognition paper by He et al. In this post we will focus on explaining how to use OCR on Android. The system is developed for deploying an easy and a secure way of taking down attendance. Bonus points in the answer if you would replace the image with text for copy/paste. Contributor Guide. Source code and demo include all needed OpenCV libs. All gists Back to GitHub. Our attribute database spans more than 700 categories and 14,000 images. We trained this model in Step 2. YOLO: Real-Time Object Detection. 3-D Face Recognition. Our CVPR 2012 paper. If you want to perform facial recognition on your Raspberry Pi today, head to the “Downloads” section of this blog post and grab the code. You can perform image segmentation, image enhancement, noise reduction, geometric transformations, image registration, and 3D image processing. First declare all variables an important objects to use:. Description In order to facilitate the study of age and gender recognition, we provide a data set and benchmark of face photos. All gists Back to GitHub. KAIST Multispectral Recognition Dataset in Day and Night. 3, ARKit has the capability to recognize 2D images. Amazon Rekognition is a simple and easy to use API that can quickly analyze any image or video file stored in Amazon S3. She serves as the reviewer of IJCV, T-PAMI, T-CSVT, T-MM, T-ITS, and CVIU, and reviewed CVPR, ICCV, ECCV from 2016 to 2018. >14 million pictures organized in >20k categories. Image recognition back-end for the popular app CamFind. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. The AIY Voice Kit from Google lets you build your own natural language processor and connect it to the Google Assistant or Cloud Speech-to-Text service, allowing you to ask questions and issue voice commands to your programs. # face_landmarks_list[0]['left_eye. Facial recognition technology, once a darling of Silicon Valley with applications for policing, spying and authenticating identities, is suddenly under fire. Please email me if you are interested. Created at Carnegie Mellon University, the developers say that it can recognize faces in real time with just 10 reference photos of the person. The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) evaluates algorithms for object detection and image classification at large scale. GitHub Gist: instantly share code, notes, and snippets. Then given a new image, compare the new face to multiple pictures of the person. 译者注: 本项目face_recognition是一个强大、简单、易上手的人脸识别开源项目,并且配备了完整的开发文档和应用案例,特别是兼容树莓派系统。. The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) evaluates algorithms for object detection and image classification at large scale. In this post, we're going to dab a little bit in machine learning and face recognition to predict if an image from a live webcam shows a smiling subject or not. Commercial quality OCR. Digital Image Processing Fall 2017 Syllabus: Image sampling and quantization, color, point operations, segmentation, morphological image processing, linear image filtering and correlation, image transforms, eigenimages, multiresolution image processing, noise reduction and restoration, feature extraction and recognition tasks, image registration. NET projects here. Learn how to perform optical character recognition (OCR) on Google Cloud Platform. 2 days ago · Get out thereand break an axle! A project log for YASP Yet-Another-Sawppy-Project. I added a second phase for this project where I used the Tensorflow Object Detection API on a custom dataset to build my own toy aeroplane detector. In this article, we provided two tutorials that illustrate how image recognition works in the TensorFlow Object Detection API. I want to preprocess image for tesseract, and I'm stuck on detection of license plate (rectangle detection). Image recognition using the Azure Custom Vision Service With the project created we then need to provide some pre-classified source images that we can upload via the interface and associate. The IBM Watson™ Visual Recognition service uses deep learning algorithms to identify scenes and objects in images that you upload to the service. I don't know how to do that. It can recognize flat objects such as covers, packaged goods or artworks. There is an open source OCR library that supports android: Tesseract. Scroll down to see it working - placeholder images from lorempixel. Same feature you can also find in Google Photoes where you can categories you image using face. Gathering a large, labeled image training set for age and gender estimation from social image repositories requires either access to personal information on the subjects ap-pearing in the images (their birth date and gender), which is often private, or is tedious and time-consuming to man-ually label. Create a new file called sample. With Raspberry Pi 3, developing a computer vision project is no longer difficult nor expensive. Github开源人脸识别项目face_recognition. Download the script from the project page on GitHub. It won the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC14). image recognition for chainer. Tutorials Find objects with a webcam. (Image Classification) Udacity's image recognition project. Analogously, the entire dataset is a (labeled) set of points. degree in the School of Data and Computer Science at Sun Yat-sen University in June 2016, advised by Prof. If you are a beginner, then it’s an amazing investment to buy a course and make use of it. CoreML Image Recognition. GitHub is the developer company. Deep Learning Projects For Beginners. I am a research scientist at FAIR. At Adobe, I work on research and tech transfer projects related to deep learning, image processing and intelligent systems. We haven't opened it on GitHub yet, but our SLAMBench suite, providing multi-platform, multi-language implementations of KinectFusion and soon other state-of-the-art SLAM algorithms might be of interest. A repository is usually used to organize a single project. Whereas visual recognition research mainly focused on two very different situations; distinguishing between basic-level categories (category recognition) or recognizing specific instances (instance recognition), developing algorithms for automatically discriminating categories with only small subtle visual differences (fine-grained recognition) is a new challenge that just started in the last. Supported languages: C, C++, C#, Python, Ruby, Java, Javascript. Amazon Rekognition is always learning from new data, and we are continually adding new labels and facial recognition features to the service. The image recognition market is estimated to grow from USD 15. This article contains a brief description of BackPropagation Artificial Neural Network and its implementation for Image Recognition. 5% of the image’s height. Flowers-Recognition. 50 Popular Python open-source projects on GitHub in 2018. GitHub Gist: instantly share code, notes, and snippets. This is just a very nice helper in the automation testing to help test something that was left for manual visual testing. There are five books which can be detected, take a look: Older news. OCR-Math - A project for quick-solving of complex math equations using image recognition. Download Project Document/Synopsis. The general-purpose API has both on-device and cloud-based models. The Pattern Recognition Application Programmer's Interface aims to be a fully-featured, easy-to-use general C++ framework for various pattern recognition tasks, especially image analysis. *The dataset is mainly designed for cross-age face recognition and retrieval. For this reason, "Issues" endpoints may return both issues and pull requests in the response. Millions of Flickr images were sucked into a database called MegaFace. Object detection is the process of finding instances of objects in images. Get results from your videos faster. It enables cloud-free image recognition. In this post we will focus on explaining how to use OCR on Android. Latest News Sept 28, 2017 - Introducing Eclipse Enterprise for Java. Back then he was. We take an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler per-pixel classification problem. CREATING ANDROID IMAGE RECOGNITION APPLICATION USING NETBEANS AND NEUROPH. AWS DeepLens sample projects are projects where the model is pre-trained so that all you have to do is create the project, import the model, deploy the project, and run the project. 3-D Face Recognition. Several sources who supposedly worked on the data collection project claim Google hired the consulting firm Randstad to collect the images with the goal of increasing the accuracy of the Pixel 4 phone's facial recognition screen unlock feature. This is a multipart post on image recognition and object detection. Image processing is the field of signal processing where both the input and output signals are images. This is an extremely competitive list and it carefully picks the best open source Machine Learning libraries, datasets and apps published between January and December 2017. Machine learning algorithm [Convolutional Neural Networks] is used to classify the image. 4 now comes with the very new FaceRecognizer class for face recognition, so you can start experimenting with face recognition right away. Where is the repo? You can fork this sample app on GitHub, or see our Getting Started sample app repos for Web. Home Hardware Software Data Other projects Learning resources About Contact. Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. Then given a new image, compare the new face to multiple pictures of the person. "- Put more images of each person (under different lighting conditions, taken on different days, etc. You can check out my article at: The API provides 5 different models that provide a trade off between speed of execution and the accuracy in placing. Provides you a simple DOM API to do voice recognition (speech to text). After loading a neural network, click on "Tap here to select image" and select an image from gallery. Xception and the Depthwise Separable Convolutions: Xception is a deep convolutional neural network architecture that involves Depthwise Separable Convolutions. ] Top Machine Learning/Data Science Packages (source: GitHub). It is a simple OCR (Optical Character Recognition) program that can convert scanned images of text back into text. In this part, we will briefly explain image recognition using traditional computer vision techniques. Neural networks are one technique which can be used for image recognition. This is just a very nice helper in the automation testing to help test something that was left for manual visual testing. Adding to the worries of privacy advocates and civil right activists in India, the country’s government is reportedly creating what is being described as the ‘world’s largest facial recognition system’. Image Processing Toolbox™ provides a comprehensive set of reference-standard algorithms and workflow apps for image processing, analysis, visualization, and algorithm development. Computer Vision and Image Understanding. The image input which you give to the system will be analyzed and the predicted result will be given as output. Find this and other hardware projects on Hackster. Facial recognition technology, once a darling of Silicon Valley with applications for policing, spying and authenticating identities, is suddenly under fire. Here are a few to consider. In recent years, I have been primarily focusing on the research fields at the intersection of computer vision, natural language processing, and temporal reasoning. So I decided to write out my results from beginning to end to detect and recognize my faces. In addition, texture recognition could be used in fingerprint recognition. This star rating then can be one of the good metrics to know the most followed projects. In the previous post, I showed you how to implement pre-trained VGG16 model, and have it recognize my testing images. NET wrapper for the Intel OpenCV image-processing library. European Conference on Computer Vision (ECCV), 2016. This isn't probably the most exciting post in here, but since I'm author of firmware for #Badge for Hackaday Conference 2018 in Belgrade , I'm often asked how to update firmware in the badge, so I decided to write it down to single place to have reference point. I was in charge of building the traffic signs recognition module and testing the hardware & software architecture. Our network architecture for face recognition is based on ResNet-34 from the Deep Residual Learning for Image Recognition paper by He et al. During the preview period, the API may change without advance notice. "- Put more images of each person (under different lighting conditions, taken on different days, etc. GitHub's icons. On a Pascal Titan X it processes images at 30 FPS and has a mAP of 57. Note: The Projects API is currently available for developers to preview. The plate's width is less than 80% of the image's width, and the plate's height is less than 87. Hello World. For questions / typos / bugs, use Piazza. Xiaogang Wang. The image above depicts Tom Ellis using the RAND tablet to interact with an onscreen image sometime in the 1960s. Have a look at the tools others are using, and the resources they are learning from. Yu Xiang's homepage Biography. Original development on the project was led by Development Seed and Mapbox as part of the 2010 Knight News Challenge. Background. Skip to content. All gists Back to GitHub. Image Recognition With TensorFlow on Raspberry Pi: Google TensorFlow is an Open-Source software Library for Numerical Computation using data flow graphs. Machine learning algorithm [Convolutional Neural Networks] is used to classify the image. The next step is to train corresponding 2 images as a good model input, and get 2 160-bit dimensional feature vector. IEEE Workshop on Analysis and Modeling of Faces and Gestures (AMFG), at the IEEE Conf. py script will then read each image file and perform this routine: For every detected object in a given image, the object is highlighted in a light-blue box, and this altered image is saved to:. Tags: medical image, image recognition, deep learning, convolutional neural networks, cnn, CNTK, image classification, lung cancer detection, boosted decision trees, LightGBM, kaggle, competition, data science bowl. IEEE International Conference on Automatic Face and Gesture Recognition, 2017. As always, I hope this project can help others find their way into the exciting world of electronics! For details and final code, please visit my GitHub depository: OpenCV-Face-Recognition. 10 Deep Learning projects based on Apache MXNet. It is not intended to be a generic DNN. We demonstrate that our alignment model produces state of the art results in retrieval experiments on Flickr8K, Flickr30K and MSCOCO datasets. I have, in fact, been procrastinating this task for a long time now and the mid-year recess was the perfect time to start a small project. Use object detection to let your cat in and out of the house with a motion-activated pet door. Object detection is the process of finding instances of objects in images. That is, instead of expressing every image as a 3072-dimensional vector where each element is the brightness of a particular pixel at some location and channel, every image above is only represented with a 144-dimensional vector, where each element measures how much of each eigenvector adds up to make up the image. Andrew Zisserman. image recognition for chainer. Create the Custom Vision service project. I hosted some projects there. He is also a honorary lecturer at the Australian National University (ANU). This demo project contains in addition other parts, like accessing the camera, handling bitmaps, making a camera focus box. You can pass in more than one image file as space-separated arguments. py, and create test data to detect and recognize my faces. https://github. The small, rectangular building sits on the northwest corner of Martin Luther King Avenue and NE 25. Download Project: >> More Projects on Image Processing with Downloads. Learn more. You might recognise Pierre’s name from a project we featured here back in April. Even though there is no R package or code to dive into this API and their API documentation is rather sparse, I thought it could be fun and inspiring to give it a try. theme deployment with GitHub Actions, which. Project Title: Cat vs Dog Image Classifier. Since we're performing image recognition, we need to provide an input of the pixels to our machine learning model. Convolutional neural networks for emotion classification from facial images as described in the following work: Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. Engineer at the scikit-learn foundation at Inria. Chih-Yao Ma's Personal Website. 2 days ago · Get out thereand break an axle! A project log for YASP Yet-Another-Sawppy-Project. This week, Google introduced a new kit for your project based on the Raspberry Pi Zero W board. Image processing is the field of signal processing where both the input and output signals are images. Minimum Requirements. Our network architecture for face recognition is based on ResNet-34 from the Deep Residual Learning for Image Recognition paper by He et al. [project webpage ]. Face recognition have been fast growing, challenging and interesting area in Continue reading →. Here's the link: https://github. Both 1 & 2 are pre-trained meaning that they are provided to you as-is by OpenCV. OpenCV is an open-source library for real-time image processing, and is used in applications like gesture mapping, motion tracking – and facial recognition. YOLO: Real-Time Object Detection. Winner in ImageNet Scene Parsing Challenge 2016 [Project & Code] Augmented Feedback in Semantic Segmentation under Image Level Supervision Xiaojuan Qi, Zhengzhe Liu, Jianping Shi, Jiaya Jia. Sai Kambampati; For reference of the demo app, you can check out the complete project on GitHub. Deep convolutional networks have become a popular tool for image generation and restoration. Now we will use our PiCam to recognize faces in real-time, as you can see below:This project was done with this fantastic "Open Source Computer Vision Library", the. VentureBeat: A few weeks ago, Jeff Bezos recommended what facial recognition legislation should look like, and then I was reading through Google’s SVP of global affairs Kent Walker gave a speech. With a little effort, this can surely. CoreML Image Recognition. Pattern recognition has applications in computer vision, radar processing, speech recognition, and text classification. IMAGE RECOGNITION WITH NEURAL NETWORKS HOWTO. So far, the recognition system has learnt the appearance of 102 different flower species which are common in the United Kingdom (see all species). Images not displaying in Github Pages? since it was the original extension of the image. Image Prcessing for Autonomous Underwater Vehicle, Robotics Club, IIT Kanpur Deisgned and developed early prototypes of an onboard image processing pipeline capable of underwater object recognition and autonomous manoeuvre. Use object detection to let your cat in and out of the house with a motion-activated pet door. Our images will be 64 pixels wide and 64 pixels high, so our probability distribution has $64\cdot 64\cdot 3 \approx 12k$ dimensions. Creating your README. Computer vision is a method of image processing and recognition that is especially useful when applied to Raspberry Pi. Import GitHub Project. Biometric recognition is the automatic recognition of a person based on one or more of these traits. During the preview period, the API may change without advance notice. Object detection is the process of finding instances of objects in images. It also stands high in researchers community. Object Recognition In Any Background Using OpenCV Python In my previous posts we learnt how to use classifiers to do Face Detection and how to create a dataset to train a and use it for Face Recognition, in this post we are will looking at how to do Object Recognition to recognize an object in an image ( for example a book), using SIFT/SURF. Due to the nature of cryptographic hashing algorithms, very tiny changes in the input file will result in a substantially different hash. The system is developed for deploying an easy and a secure way of taking down attendance. I was just looking for a sample working code. A noise removal function is underway. WhatsApp Share Tweet. GitHub Gist: instantly share code, notes, and snippets. Here we will train model with 6 classes of Bollywood actor and. Apple's ARKit 1. Shihao Zhang, Huazhu Fu, Yuguang Yan, Yubing Zhang, Qingyao Wu, Ming Yang, Mingkui Tan, Yanwu Xu, ~NEW "Attention Guided Network for Retinal Image Segmentation", in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. Real Time Object Recognition (Part 2) 6 minute read So here we are again, in the second part of my Real time Object Recognition project. Funkhouser Proceedings of 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR2017) Oral Presentation [Watch it on Youtube] · Paper · Project Webpage. VentureBeat: A few weeks ago, Jeff Bezos recommended what facial recognition legislation should look like, and then I was reading through Google’s SVP of global affairs Kent Walker gave a speech. A couple of weeks ago Google announced their vision API providing some similar features. To do this, the sources claim, Randstad sent data collectors to Atlanta and specifically targeted. We trained this model in Step 2. 100+ Projects in Image Processing and Fingerprint Recognition. Previously, I received the B. flandmark (version 1. py --image_file images. https://github. This is a multipart post on image recognition and object detection. 3K stars fo-dicom. Please check the project webpage. Viable GitHub alternatives. NET, Microsoft Azure App Service, Azure SQL Database, and Microsoft Cognitive Services. Using the code. This week we are going to talk about image recognition in augmented reality. Download Project Document/Synopsis. Gathering a large, labeled image training set for age and gender estimation from social image repositories requires either access to personal information on the subjects ap-pearing in the images (their birth date and gender), which is often private, or is tedious and time-consuming to man-ually label. This section contains links to documents which describe how to use Sphinx to recognize speech. RoogleVision released - a Package for Image Recognition First to the naming; it basically is an arbitrary condensation of “R + Google Cloud Vision API”. Home Hardware Software Data Other projects Learning resources About Contact. Engineer at the scikit-learn foundation at Inria. The next step is to train corresponding 2 images as a good model input, and get 2 160-bit dimensional feature vector. Badge URLs for both private and public projects contain a security token. This article contains a brief description of BackPropagation Artificial Neural Network and its implementation for Image Recognition. The library is quite intensive on the processor. NET wrapper for the Intel OpenCV image-processing library.