Face Detection and Recognition System (FDRS) is a physical characteristics recognition technology, using the inherent physiological features of humans for ID recognition. The technology does not need to be carried about and will not be lost, so it is convenient and safe for use
Introduction to Computer Vision using OpenCVDylan Seychell
This is an introductory deck to computer vision using OpenCV and Python, through examples. This presentation is a step by step codelab through the basic functions of OpenCV.
Face Detection and Recognition System (FDRS) is a physical characteristics recognition technology, using the inherent physiological features of humans for ID recognition. The technology does not need to be carried about and will not be lost, so it is convenient and safe for use
Introduction to Computer Vision using OpenCVDylan Seychell
This is an introductory deck to computer vision using OpenCV and Python, through examples. This presentation is a step by step codelab through the basic functions of OpenCV.
This is the first part of the presentation series on one of the powerful open sources libraries, the opencv. this presentation is about the introduction, installation, some basic functions on images and some basic image processing on the images
Artificial Intelligence, Machine Learning, Deep Learning
The 5 myths of AI
Deep Learning in action
Basics of Deep Learning
NVIDIA Volta V100 and AWS P3
Deep Learning Tutorial | Deep Learning Tutorial For Beginners | What Is Deep ...Simplilearn
This presentation about Deep Learning is designed for beginners who want to learn Deep Learning from scratch. We will look at where Deep Learning is applied and what exactly this term means. We'll see how Deep Learning, Machine Learning, and AI are different and why Deep Learning even came into the picture. We will then proceed to look at Neural Networks, which are the core of Deep Learning. Before we move into the working of Neural Networks, we'll cover activation and cost functions. The video will also introduce you to the most popular Deep Learning platforms. We wrap it up with a demo in TensorFlow to predict if a person receives a salary above or below 50k. Now, let us get started and understand Deep Learning in detail.
Below topics are explained in this Deep Learning presentation:
1. Applications of Deep Learning
2. What is Deep Learning
3. Why is Deep Learning important
4. What are Neural Networks
5. Activation function
6. Cost function
7. How do Neural Networks work
8. Deep Learning platforms
9. Introduction to TensorFlow
10. Use case implementation using TensorFlow
Why Deep Learning?
It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you build and implement artificial Neural Networks.
Advancements in Deep Learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in Deep Learning models, learn to operate TensorFlow to manage Neural Networks and interpret the results. According to payscale.com, the median salary for engineers with Deep Learning skills tops $120,000 per year.
You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement Deep Learning algorithms, understand Neural Networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional Neural Networks, Recurrent Neural Networks, training deep networks and high-level interfaces
4. Build Deep Learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of Artificial Neural Networks
6. Troubleshoot and improve Deep Learning models
Learn more at https://www.simplilearn.com/deep-learning-course-with-tensorflow-training
DEEPFAKE DETECTION TECHNIQUES: A REVIEWvivatechijri
Noteworthy advancements in the field of deep learning have led to the rise of highly realistic AI generated fake videos, these videos are commonly known as Deepfakes. They refer to manipulated videos, that are generated by sophisticated AI, that yield formed videos and tones that seem to be original. Although this technology has numerous beneficial applications, there are also significant concerns about the disadvantages of the same. So there is a need to develop a system that would detect and mitigate the negative impact of these AI generated videos on society. The videos that get transferred through social media are of low quality, so the detection of such videos becomes difficult. Many researchers in the past have done analysis on Deepfake detection which were based on Machine Learning, Support Vector Machine and Deep Learning based techniques such as Convolution Neural Network with or without LSTM .This paper analyses various techniques that are used by several researchers to detect Deepfake videos.
Overview of Computer Vision For Footwear IndustryTanvir Moin
Computer vision is an interdisciplinary field that focuses on enabling computers to interpret and analyze visual data from the world around us. It involves the development of algorithms and techniques that allow machines to understand images and videos, just as humans do.
The main goal of computer vision is to create machines that can "see" and understand the world around them, and then use that information to make decisions or take actions. This can involve tasks such as object recognition, scene reconstruction, facial recognition, and image segmentation.
Computer vision has a wide range of applications in various fields, such as healthcare, entertainment, transportation, robotics, and security. Some examples include medical image analysis, autonomous vehicles, augmented reality, and surveillance systems.
In recent years, the development of deep learning techniques, particularly convolutional neural networks (CNNs), has greatly advanced the field of computer vision, allowing machines to achieve state-of-the-art performance on various visual recognition tasks.
Introduction to Artificial Intelligence | AI using Deep Learning | EdurekaEdureka!
This slide on Artificial intelligence will give you an introduction to artificial intelligence with futuristic applications of AI. It also tells you how to implement artificial intelligence using deep neural networks.
The slide covers the following topics:
1. What is Artificial Intelligence & its applications
2. Subsets of AI - Machine Learning & Deep Learning
3. What is Deep Learning?
4. Use Case - Recognizing handwritten digits from MNIST dataset
5. Applications of Deep Learning
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2015-embedded-vision-summit-opencv
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Gary Bradski, President and CEO of the OpenCV Foundation, presents the "OpenCV Open Source Computer Vision Library: Latest Developments" tutorial at the May 2015 Embedded Vision Summit.
OpenCV is an enormously popular open source computer vision library, with over 9 million downloads. Originally used mainly for research and prototyping, in recent years OpenCV has increasingly been used in deployed products on a wide range of platforms from cloud to mobile.
The latest version, OpenCV 3.0 is currently in beta, and is a major overhaul, bringing OpenCV up to modern C++ standards and incorporating expanded support for 3D vision. The new release also introduces a modular “contrib” facility that enables independently developed modules to be quickly integrated with OpenCV as needed, providing a flexible mechanism to allow developers to experiment with new techniques before they are officially integrated into the library.
In this talk, Gary Bradski, head of the OpenCV Foundation, provides an insider’s perspective on the new version of OpenCV and how developers can utilize it to maximum advantage for vision research, prototyping, and product development.
This is the first part of the presentation series on one of the powerful open sources libraries, the opencv. this presentation is about the introduction, installation, some basic functions on images and some basic image processing on the images
Artificial Intelligence, Machine Learning, Deep Learning
The 5 myths of AI
Deep Learning in action
Basics of Deep Learning
NVIDIA Volta V100 and AWS P3
Deep Learning Tutorial | Deep Learning Tutorial For Beginners | What Is Deep ...Simplilearn
This presentation about Deep Learning is designed for beginners who want to learn Deep Learning from scratch. We will look at where Deep Learning is applied and what exactly this term means. We'll see how Deep Learning, Machine Learning, and AI are different and why Deep Learning even came into the picture. We will then proceed to look at Neural Networks, which are the core of Deep Learning. Before we move into the working of Neural Networks, we'll cover activation and cost functions. The video will also introduce you to the most popular Deep Learning platforms. We wrap it up with a demo in TensorFlow to predict if a person receives a salary above or below 50k. Now, let us get started and understand Deep Learning in detail.
Below topics are explained in this Deep Learning presentation:
1. Applications of Deep Learning
2. What is Deep Learning
3. Why is Deep Learning important
4. What are Neural Networks
5. Activation function
6. Cost function
7. How do Neural Networks work
8. Deep Learning platforms
9. Introduction to TensorFlow
10. Use case implementation using TensorFlow
Why Deep Learning?
It is one of the most popular software platforms used for Deep Learning and contains powerful tools to help you build and implement artificial Neural Networks.
Advancements in Deep Learning are being seen in smartphone applications, creating efficiencies in the power grid, driving advancements in healthcare, improving agricultural yields, and helping us find solutions to climate change. With this Tensorflow course, you’ll build expertise in Deep Learning models, learn to operate TensorFlow to manage Neural Networks and interpret the results. According to payscale.com, the median salary for engineers with Deep Learning skills tops $120,000 per year.
You can gain in-depth knowledge of Deep Learning by taking our Deep Learning certification training course. With Simplilearn’s Deep Learning course, you will prepare for a career as a Deep Learning engineer as you master concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms. Those who complete the course will be able to:
1. Understand the concepts of TensorFlow, its main functions, operations and the execution pipeline
2. Implement Deep Learning algorithms, understand Neural Networks and traverse the layers of data abstraction which will empower you to understand data like never before
3. Master and comprehend advanced topics such as convolutional Neural Networks, Recurrent Neural Networks, training deep networks and high-level interfaces
4. Build Deep Learning models in TensorFlow and interpret the results
5. Understand the language and fundamental concepts of Artificial Neural Networks
6. Troubleshoot and improve Deep Learning models
Learn more at https://www.simplilearn.com/deep-learning-course-with-tensorflow-training
DEEPFAKE DETECTION TECHNIQUES: A REVIEWvivatechijri
Noteworthy advancements in the field of deep learning have led to the rise of highly realistic AI generated fake videos, these videos are commonly known as Deepfakes. They refer to manipulated videos, that are generated by sophisticated AI, that yield formed videos and tones that seem to be original. Although this technology has numerous beneficial applications, there are also significant concerns about the disadvantages of the same. So there is a need to develop a system that would detect and mitigate the negative impact of these AI generated videos on society. The videos that get transferred through social media are of low quality, so the detection of such videos becomes difficult. Many researchers in the past have done analysis on Deepfake detection which were based on Machine Learning, Support Vector Machine and Deep Learning based techniques such as Convolution Neural Network with or without LSTM .This paper analyses various techniques that are used by several researchers to detect Deepfake videos.
Overview of Computer Vision For Footwear IndustryTanvir Moin
Computer vision is an interdisciplinary field that focuses on enabling computers to interpret and analyze visual data from the world around us. It involves the development of algorithms and techniques that allow machines to understand images and videos, just as humans do.
The main goal of computer vision is to create machines that can "see" and understand the world around them, and then use that information to make decisions or take actions. This can involve tasks such as object recognition, scene reconstruction, facial recognition, and image segmentation.
Computer vision has a wide range of applications in various fields, such as healthcare, entertainment, transportation, robotics, and security. Some examples include medical image analysis, autonomous vehicles, augmented reality, and surveillance systems.
In recent years, the development of deep learning techniques, particularly convolutional neural networks (CNNs), has greatly advanced the field of computer vision, allowing machines to achieve state-of-the-art performance on various visual recognition tasks.
Introduction to Artificial Intelligence | AI using Deep Learning | EdurekaEdureka!
This slide on Artificial intelligence will give you an introduction to artificial intelligence with futuristic applications of AI. It also tells you how to implement artificial intelligence using deep neural networks.
The slide covers the following topics:
1. What is Artificial Intelligence & its applications
2. Subsets of AI - Machine Learning & Deep Learning
3. What is Deep Learning?
4. Use Case - Recognizing handwritten digits from MNIST dataset
5. Applications of Deep Learning
For the full video of this presentation, please visit:
http://www.embedded-vision.com/platinum-members/embedded-vision-alliance/embedded-vision-training/videos/pages/may-2015-embedded-vision-summit-opencv
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Gary Bradski, President and CEO of the OpenCV Foundation, presents the "OpenCV Open Source Computer Vision Library: Latest Developments" tutorial at the May 2015 Embedded Vision Summit.
OpenCV is an enormously popular open source computer vision library, with over 9 million downloads. Originally used mainly for research and prototyping, in recent years OpenCV has increasingly been used in deployed products on a wide range of platforms from cloud to mobile.
The latest version, OpenCV 3.0 is currently in beta, and is a major overhaul, bringing OpenCV up to modern C++ standards and incorporating expanded support for 3D vision. The new release also introduces a modular “contrib” facility that enables independently developed modules to be quickly integrated with OpenCV as needed, providing a flexible mechanism to allow developers to experiment with new techniques before they are officially integrated into the library.
In this talk, Gary Bradski, head of the OpenCV Foundation, provides an insider’s perspective on the new version of OpenCV and how developers can utilize it to maximum advantage for vision research, prototyping, and product development.
For the full video of this presentation, please visit:
https://www.edge-ai-vision.com/2020/03/opencv-past-present-and-future-a-presentation-from-opencv-org/
For more information about edge AI and vision, please visit:
http://www.edge-ai-vision.com
Gary Bradski, the President and CEO of OpenCV.org, delivers the presentation “OpenCV: Past, Present and Future” at the Edge AI and Vision Alliance’s March 2020 Vision Industry and Technology Forum. Bradski shares the latest developments in the OpenCV open source library for computer vision and deep learning applications, as well as where OpenCV is heading.
This manual is “How to Build” manual for OpenCV with OpenCL for Android.
If you want to “Use OpenCL on OpenCV” ONLY,
Please see
http://github.com/noritsuna/OpenCVwithOpenCL4AndroidNDKSample
GeoServer is an amazing project, and an amazing project to work on!
Please attend this workshop to:
* Get Started with the GeoServer codebase
* Orientation with a Tour of the GeoServer architecture
* Introduction the service dispatch framework, includin creating your own service
* Built chain and test facilities
* Create a custom function for use with map styling
* Create a custom process for use with style transformations and web processing service
* Anatomy of a successful pull request
Attendees will build their own GeoServer, learn a bit about how our community operates, and enjoy extending the base application.
If you are a developer looking to support GeoServer, or join us for a sprint or bug-stomp, this workshop is great introduction.
This course features hands-on development. We encourage and expect you to bring your favourite Java development environment.
For a good time with open source join GeoServer today!
Here is my slide on OpenCV. This slide includes major things about OpenCV such as what is OpenCV?, its appications, Functionalities, uses, pros and cons, Modules of OpenCV and Installation of OpenCV in all platforms.
Avoid the Vendor Lock-in Trap (with App Deployment)Peter Bittner
There is no such thing as "marriage" in business. When you're not happy with the service or pricing you move on. But at what price? Switching a technology is hard, switching a platform is harder! Simply follow a set of principles and techniques to ensure your freedom and agility.
Настройка окружения для кросскомпиляции проектов на основе docker'acorehard_by
Как быстро и легко настраивать/обновлять окружения для кросскомпиляции проектов под различные платформы(на основе docker), как быстро переключаться между ними, как используя эти кирпичики организовать CI и тестирование(на основе GitLab и Docker).
This talk describes the current state of the Veil-Framework and the different tools included in it such as Veil-Evasion, Veil-Catapult, Veil-Powerview, Veil-Pillage, Veil-Ordnance
The Future of Security and Productivity in Our Newly Remote WorldDevOps.com
Andy has made mistakes. He's seen even more. And in this talk he details the best and the worst of the container and Kubernetes security problems he's experienced, exploited, and remediated.
This talk details low level exploitable issues with container and Kubernetes deployments. We focus on lessons learned, and show attendees how to ensure that they do not fall victim to avoidable attacks.
See how to bypass security controls and exploit insecure defaults in this technical appraisal of the container and cluster security landscape.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/intel/embedded-vision-training/videos/pages/may-2017-embedded-vision-summit-pisarevsky
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Vadim Pisarevsky, Software Engineering Manager at Intel, presents the "Making OpenCV Code Run Fast" tutorial at the May 2017 Embedded Vision Summit.
OpenCV is the de facto standard framework for computer vision developers, with a 16+ year history, approximately one million lines of code, thousands of algorithms and tens of thousands of unit tests. While OpenCV delivers decent performance out-of-the-box for some classical algorithms on desktop PCs, it lacks sufficient performance when using some modern algorithms, such as deep neural networks, and when running on embedded platforms. Pisarevsky examines current and forthcoming approaches to performance optimization of OpenCV, including the existing OpenCL-based transparent API, newly added support for OpenVX, and early experimental results using Halide.
He demonstrates the use of the OpenCL-based transparent API on a popular CV problem: pedestrian detection. Because OpenCL does not provide good performance-portability, he explores additional approaches. He discusses how OpenVX support in OpenCV accelerates image processing pipelines and deep neural network execution. He also presents early experimental results using Halide, which provides a higher level of abstraction and ease of use, and is being actively considered for future support in OpenCV.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Globus Compute wth IRI Workflows - GlobusWorld 2024Globus
As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
We describe the deployment and use of Globus Compute for remote computation. This content is aimed at researchers who wish to compute on remote resources using a unified programming interface, as well as system administrators who will deploy and operate Globus Compute services on their research computing infrastructure.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Check out the webinar slides to learn more about how XfilesPro transforms Salesforce document management by leveraging its world-class applications. For more details, please connect with sales@xfilespro.com
If you want to watch the on-demand webinar, please click here: https://www.xfilespro.com/webinars/salesforce-document-management-2-0-smarter-faster-better/
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
2. About OpenCV
●
Open Source Computer Vision library
●
Real-time Computer vision library
●
Started by Intel Russia, launched in 1999
●
2000 : First alpha release
●
2006: First stable release
●
2009: Second major release
http://www.qboticslabs.com
3. About OpenCV
●
2012 : opencv -> opencv.org
●
Current version : OpenCV 3.0 beta
●
Opensource BSD license
●
Cross platform
●
Now supporting by Willow Garage and Itseez
http://www.qboticslabs.com
4. About OpenCV
●
Written in C++ and C
●
Full Interfaces for Python, Java, Matlab/
Octave
●
Wrappers in C#, Perl, Ruby
●
OS Support : Windows, Linux, Android, Maemo,
FreeBSD, IOS, OS X, BlackBerry 10
http://www.qboticslabs.com
5. Applications of OpenCV
●
Gesture recognition
●
Human-computer interaction(HCI)
●
Mobile robotics
●
Segmentation and recognition
●
Motion tracking
●
Augmented reality
●
Machine learning
http://www.qboticslabs.com
24. Compile code without Eclipse
●
Save code as .cpp using an text editor
●
Compile using following command
● $ g++ <input_file.cpp> `pkg-config
opencv –cflags –libs` -o
<output_name>
● $ ./output_name
25. OpenCV Modules
●
OpenCV has modular structure
●
OpenCV contain several shared/static libraries
● Core : Contain basic image data structure such as
Mat
● Imgproc : image processing module contain linear
and non linear filter, color space conversion,
histogram etc
● Video : Motion estimation, background substraction,
object tracking algorithms etc
26. OpenCV Modules
● Calib3d : mainly for camera calibration
● Features2d : contain feature detectors,
descriptors and descriptor matchers
● Objdetect: contain object detection algorithms
● Highgui: contain UI functionality to handle video
and image
● Gpu : GPU-accelerated algorithms
31. Reading a Video
OpenCV Header Files Used
● #include <opencv2/highgui/highgui.hpp>
OpenCV API's used
● VideoCapture cap(argv[1])
● waitKey(30)
32. Reading from Camera
OpenCV Header Files Used
● #include <opencv2/highgui/highgui.hpp>
OpenCV API's used
● VideoCapture cap(argv[1])
● waitKey(30)
33. Reading Pixel from Image and
Mouse Interaction
OpenCV Header Files Used
● #include <opencv2/highgui/highgui.hpp>
OpenCV API's used
● image.at<uchar>(y,x);
● image.at<Vec3b>(y,x)[0];
● setMouseCallback("Display window",
mouse_callback, NULL);
34. Working with Mat type
OpenCV Header Files Used
● #include <opencv2/highgui/highgui.hpp>
OpenCV API's used
● Mat red(480,640,CV_8UC3,Scalar(0,0,255));
● imwrite("red.jpg",red);
35. Adjusting brightness and contrast
OpenCV Header Files Used
● #include <opencv2/highgui/highgui.hpp>
OpenCV API's used
● new_image.at<Vec3b>(y,x)[c] =
saturate_cast<uchar>( alpha*( image.at<Vec3b>(y
,x)[c] ) + beta );
● Alpha = contrast
● Beta = Brightness
● saturate_cast ensure value is valid or not