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Tag: Vision

  • Robotics, Vision and Control: Fundamental Algorithms in Python (Springer Tracts in Advanced Robotics Book 146)

    Robotics, Vision and Control: Fundamental Algorithms in Python (Springer Tracts in Advanced Robotics Book 146)


    Price: $69.52
    (as of Dec 24,2024 17:55:14 UTC – Details)



    Are you interested in learning about the fundamental algorithms in robotics, vision, and control? Look no further than the book “Robotics, Vision and Control: Fundamental Algorithms in Python (Springer Tracts in Advanced Robotics Book 146)”.

    This comprehensive book covers a wide range of topics, including robot kinematics, dynamics, motion planning, and computer vision. With a focus on practical applications and hands-on examples, readers will learn how to implement these algorithms in Python to solve real-world problems.

    Whether you are a beginner or an advanced researcher in the field of robotics, this book is a valuable resource for understanding the key concepts and techniques in robotics, vision, and control. Get your copy today and start mastering the fundamentals of robotics with Python!
    #Robotics #Vision #Control #Fundamental #Algorithms #Python #Springer #Tracts #Advanced #Robotics #Book

  • Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library

    Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library


    Price: $84.99 – $51.10
    (as of Dec 24,2024 17:54:15 UTC – Details)




    Publisher ‏ : ‎ O’Reilly Media; 1st edition (February 7, 2017)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 1022 pages
    ISBN-10 ‏ : ‎ 1491937998
    ISBN-13 ‏ : ‎ 978-1491937990
    Item Weight ‏ : ‎ 1.47 pounds
    Dimensions ‏ : ‎ 5.91 x 0.59 x 9.84 inches


    Are you interested in diving into the world of computer vision and image processing? Look no further than OpenCV 3! OpenCV is a powerful open-source library for computer vision, image processing, and machine learning, and with its latest version, OpenCV 3, there are even more features and improvements to take advantage of.

    In our upcoming series, we will be exploring how to use OpenCV 3 with C++ to develop applications for tasks such as object detection, facial recognition, image segmentation, and more. Whether you are a beginner looking to learn the basics of computer vision or an experienced developer looking to enhance your skills, this series is perfect for you.

    Stay tuned for tutorials, code samples, and projects to help you master OpenCV 3 and unleash the full potential of computer vision in your applications. Get ready to see the world through the eyes of a computer with OpenCV 3! #OpenCV #ComputerVision #C++ #ImageProcessing #MachineLearning
    #Learning #OpenCV #Computer #Vision #OpenCV #Library

  • Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition)

    Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition)


    Price: $88.00
    (as of Dec 24,2024 17:13:03 UTC – Details)



    Computer vision is an exciting field that is constantly evolving with new advancements in technology. One of the most cutting-edge techniques in computer vision is deep learning, a subset of machine learning that uses neural networks to analyze and interpret visual data.

    Advanced methods in computer vision, such as deep learning, have revolutionized the way we approach image and video analysis. These methods have allowed for more accurate object recognition, image segmentation, and scene understanding.

    Deep learning algorithms are able to learn complex patterns and features from large amounts of visual data, making them highly effective in tasks such as image classification, object detection, and image generation.

    In the field of computer vision and pattern recognition, researchers are constantly exploring new ways to improve the performance of deep learning models. Techniques such as transfer learning, data augmentation, and adversarial training are being used to enhance the capabilities of deep learning algorithms.

    Advancements in computer vision are being applied to a wide range of industries, including healthcare, automotive, and security. From medical image analysis to autonomous vehicles, deep learning in computer vision is revolutionizing the way we interact with visual data.

    As researchers continue to push the boundaries of computer vision technology, we can expect to see even more exciting advancements in the field. The future of computer vision is bright, and deep learning is paving the way for more intelligent and efficient visual analysis.
    #Advanced #Methods #Deep #Learning #Computer #Vision #Computer #Vision #Pattern #Recognition

  • Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3, 2nd Edition

    Raspberry Pi Computer Vision Programming: Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3, 2nd Edition


    Price: $17.97
    (as of Dec 24,2024 16:33:02 UTC – Details)




    ASIN ‏ : ‎ B085P1HWPM
    Publisher ‏ : ‎ Packt Publishing; 2nd edition (June 29, 2020)
    Publication date ‏ : ‎ June 29, 2020
    Language ‏ : ‎ English
    File size ‏ : ‎ 25796 KB
    Text-to-Speech ‏ : ‎ Enabled
    Screen Reader ‏ : ‎ Supported
    Enhanced typesetting ‏ : ‎ Enabled
    X-Ray ‏ : ‎ Not Enabled
    Word Wise ‏ : ‎ Not Enabled
    Print length ‏ : ‎ 306 pages


    If you’re looking to dive into the world of computer vision programming using Raspberry Pi, OpenCV, and Python 3, then the newly released 2nd edition of “Raspberry Pi Computer Vision Programming” is the perfect guide for you.

    This comprehensive book covers everything you need to know to design and implement computer vision applications on the popular Raspberry Pi platform. From setting up your Raspberry Pi and installing OpenCV to creating your own image processing and object detection programs, this book walks you through the entire process step by step.

    With practical examples and hands-on projects, you’ll learn how to harness the power of Raspberry Pi and OpenCV to build real-world computer vision applications. Whether you’re a beginner looking to get started with computer vision programming or a seasoned developer looking to expand your skills, this book has something for everyone.

    So grab your Raspberry Pi, fire up your Python interpreter, and get ready to unlock the full potential of computer vision programming with “Raspberry Pi Computer Vision Programming, 2nd Edition”.
    #Raspberry #Computer #Vision #Programming #Design #implement #computer #vision #applications #Raspberry #OpenCV #Python #2nd #Edition

  • Building Computer Vision Projects with OpenCV 4 and C++

    Building Computer Vision Projects with OpenCV 4 and C++


    Price: $49.99 – $47.42
    (as of Dec 24,2024 15:49:39 UTC – Details)




    Publisher ‏ : ‎ Packt Publishing (March 22, 2019)
    Language ‏ : ‎ English
    Paperback ‏ : ‎ 538 pages
    ISBN-10 ‏ : ‎ 1838644679
    ISBN-13 ‏ : ‎ 978-1838644673
    Item Weight ‏ : ‎ 2.05 pounds
    Dimensions ‏ : ‎ 9.25 x 7.5 x 1.11 inches


    Building Computer Vision Projects with OpenCV 4 and C++

    Are you interested in diving into the world of computer vision and creating projects using OpenCV 4 and C++? Look no further! In this post, we will explore how you can start building your own computer vision projects using the powerful combination of OpenCV 4 and C++.

    OpenCV 4 is a popular open-source computer vision and machine learning software library that provides tools and algorithms for image and video processing. With the recent release of OpenCV 4, developers have access to even more features and improvements for their computer vision projects.

    To get started with building computer vision projects using OpenCV 4 and C++, you will need to have a basic understanding of C++ programming and some knowledge of computer vision concepts. If you are new to C++ or computer vision, there are plenty of resources available online to help you get up to speed.

    Once you have a good grasp of C++ and computer vision fundamentals, you can begin exploring the various functionalities of OpenCV 4. Some popular projects that you can build using OpenCV 4 and C++ include object detection, facial recognition, image segmentation, and more.

    To start building your own computer vision project, you can download and install OpenCV 4 from the official website and set up your development environment. You can then begin writing C++ code to implement the desired functionality, using the OpenCV 4 library functions and algorithms.

    Overall, building computer vision projects with OpenCV 4 and C++ can be a rewarding and exciting experience. With the powerful tools and capabilities of OpenCV 4, you can create sophisticated computer vision applications that can analyze and process images and videos in real-time. So why wait? Start exploring the world of computer vision today with OpenCV 4 and C++!
    #Building #Computer #Vision #Projects #OpenCV

  • Image Classification: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning

    Image Classification: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning


    Price: $9.95
    (as of Dec 24,2024 15:21:54 UTC – Details)




    ASIN ‏ : ‎ B07NKT94GV
    Publisher ‏ : ‎ M.J. Magic Publishing; 1st edition (February 9, 2019)
    Publication date ‏ : ‎ February 9, 2019
    Language ‏ : ‎ English
    File size ‏ : ‎ 4207 KB
    Text-to-Speech ‏ : ‎ Not enabled
    Enhanced typesetting ‏ : ‎ Not Enabled
    X-Ray ‏ : ‎ Not Enabled
    Word Wise ‏ : ‎ Not Enabled
    Format ‏ : ‎ Print Replica


    Image Classification: Step-by-step Classifying Images with Python and Techniques of Computer Vision and Machine Learning

    In this post, we will explore the process of image classification using Python and popular techniques of computer vision and machine learning. Image classification is the task of assigning a label or category to an image based on its content. This task is commonly used in various fields such as healthcare, autonomous driving, and security.

    To classify images, we will be using the following steps:

    1. Data Collection: The first step in image classification is to gather a dataset of images that are labeled with their corresponding categories. This dataset will be used to train our machine learning model.

    2. Data Preprocessing: Before feeding the images into the model, we need to preprocess them by resizing, normalizing, and augmenting the data to improve the model’s performance.

    3. Model Building: We will build a convolutional neural network (CNN) using popular libraries such as TensorFlow or PyTorch. CNNs are widely used in image classification tasks due to their ability to learn spatial hierarchies of features.

    4. Model Training: We will train the CNN model on our dataset using techniques such as backpropagation and stochastic gradient descent to optimize the model’s parameters.

    5. Model Evaluation: Once the model is trained, we will evaluate its performance on a separate test dataset to measure its accuracy, precision, recall, and F1 score.

    6. Prediction: Finally, we will use the trained model to classify new images and make predictions on their categories.

    By following these steps and utilizing the power of computer vision and machine learning techniques, we can successfully classify images with Python. Stay tuned for the upcoming tutorials where we will dive deeper into each of these steps and provide code examples to help you get started with image classification.
    #Image #Classification #Stepbystep #Classifying #Images #Python #Techniques #Computer #Vision #Machine #Learning

  • MakerFocus Raspberry Pi 4 Camera 5MP OV5647 Fisheye Camera Automatically Switching Between Day and Night Vision IR-Cut Webcam Compatible with Raspberry Pi 4B/3B+/3B/2B

    MakerFocus Raspberry Pi 4 Camera 5MP OV5647 Fisheye Camera Automatically Switching Between Day and Night Vision IR-Cut Webcam Compatible with Raspberry Pi 4B/3B+/3B/2B


    Price: $319.00 – $21.99
    (as of Dec 24,2024 15:14:43 UTC – Details)



    Please Note:
    The LED fill lights on both sides will warm up(generally in 40 to 50℃) when they working, but it is normal, please don’t worry, they can keep working 20 hours, it will not damage the camera normally. You can adjust the micro adjustable resistor(beside the lights) to turned down the lights to Lower temperatures.

    Description:
    The camera is equipped with photosensitive resistance, which enables the camera to automatically detect and recognize light to automatically switch between the night-vision and day-time shooting mode. Manual settings are not required, plug-in then it can be used. The advantage is that during the day, the photographs taken will not be reddish, which also eliminates the need for manual switching.

    Specifications:
    Infrared Camera:
    Pixels: 5 Megapixels
    Photosensitive chip: OV5647
    Focal Length: 1.7 mm
    Aperture (F) : 2.0
    FOV (Diagonal): 175 degrees
    Sensor optimum resolution: 1080P
    Size: 11.7 * 6.6 * 3.6 cm
    Product weight: 0.028kg Infrared Light: can fill flash

    Photoresistor: to detect ambient light intensity

    Package Content:
    1 * Fisheye Infrared Camera
    2 * LED Lights
    1 * 15cm FFC Cable
    4 * Screws and Nuts
    Please note: The LED fill lights on both sides will warm up(generally in 40 to 50℃) when they working, but it is normal, please don’t worry, they can keep working 20 hours, it will not damage the camera normally. You can adjust the micro adjustable resistor(beside the lights) to turned down the lights to Lower temperatures
    The camera is equipped with photosensitive resistance, built in IR-CUT, which enables the camera to automatically detect and recognize light to automatically switch between the night-vision and day-time shooting mode. Manual settings are not required, plug-in then it can be used. The advantage is that during the day, the photographs taken will not be reddish, which also eliminates the need for manual switching
    This is a Fisheye ( Wide Angle )175 degrees IR Camera for Raspberry Pi 4B/3B+/3B/2B. You can use it to take a wide angle picture or video by this camera
    5 Megapixels OV5647 Sensor, Support 1080P resolution; 2.0 Aperture (F),1.7 mm focal length. Suitabl for Surveillance Camera
    We Have a Strong After-sales Service Team: As long as you have any questions about the product, we will resolve your issue immediately if received your email, your satisfactory purchase experience is our greatest hope! How to email us? Plz click “MakerFocus” and click “Ask a question” to email us! Looking for your consultation

    Customers say

    Customers are satisfied with the camcorder’s quality, night vision, and value for money. They mention it works great with Octopi and has good video quality both in light and dark. Many appreciate the wide angle and ease of setup. However, some dislike the heat level. Opinions vary on functionality and resolution.

    AI-generated from the text of customer reviews


    MakerFocus Raspberry Pi 4 Camera: Your Ultimate Day and Night Vision Companion!

    Introducing the MakerFocus Raspberry Pi 4 Camera, equipped with a high-quality 5MP OV5647 fisheye lens that captures crystal clear images and videos. This camera is designed to automatically switch between day and night vision, thanks to its IR-Cut feature that ensures optimal performance in any lighting conditions.

    Compatible with Raspberry Pi 4B/3B+/3B/2B, this webcam is easy to install and operate, making it the perfect accessory for your Raspberry Pi projects. Whether you’re monitoring your home, capturing wildlife footage, or creating time-lapse videos, the MakerFocus Raspberry Pi 4 Camera is versatile and reliable.

    Don’t miss out on the opportunity to enhance your Raspberry Pi experience with this high-performance camera. Get yours today and start capturing stunning visuals with ease!
    #MakerFocus #Raspberry #Camera #5MP #OV5647 #Fisheye #Camera #Automatically #Switching #Day #Night #Vision #IRCut #Webcam #Compatible #Raspberry #4B3B3B2B,with 5mp webcam

  • Mastering Computer Vision with PyTorch and Machine Learning

    Mastering Computer Vision with PyTorch and Machine Learning


    Price: $120.00 – $90.39
    (as of Dec 24,2024 15:07:28 UTC – Details)




    Publisher ‏ : ‎ Iop Publishing Ltd (September 20, 2024)
    Language ‏ : ‎ English
    Hardcover ‏ : ‎ 364 pages
    ISBN-10 ‏ : ‎ 0750362421
    ISBN-13 ‏ : ‎ 978-0750362429
    Item Weight ‏ : ‎ 1.87 pounds
    Dimensions ‏ : ‎ 7.35 x 1 x 10.3 inches


    Are you ready to take your computer vision skills to the next level? Join us for an intensive workshop on mastering computer vision with PyTorch and machine learning. In this hands-on session, you will learn how to build and train deep learning models for image recognition, object detection, and more using the powerful PyTorch framework.

    Our expert instructors will guide you through the fundamentals of computer vision, including image preprocessing, data augmentation, and model evaluation. You will also have the opportunity to work on real-world projects and gain practical experience in applying computer vision techniques to solve complex problems.

    Whether you are a seasoned machine learning practitioner or a beginner looking to dive into the world of computer vision, this workshop is perfect for anyone who wants to enhance their skills and stay ahead in this rapidly evolving field. Don’t miss out on this opportunity to become a master of computer vision with PyTorch and machine learning. Sign up now and take your career to new heights!
    #Mastering #Computer #Vision #PyTorch #Machine #Learning

  • Hands-On Computer Vision with Detectron2: Develop object detection and segmentation models with a code and visualization approach

    Hands-On Computer Vision with Detectron2: Develop object detection and segmentation models with a code and visualization approach


    Price: $43.13
    (as of Dec 24,2024 14:26:14 UTC – Details)



    Hands-On Computer Vision with Detectron2: Develop object detection and segmentation models with a code and visualization approach

    In this post, we will explore how to build advanced computer vision models using Detectron2, a powerful open-source framework for object detection and segmentation developed by Facebook AI Research. With Detectron2, you can easily train and deploy state-of-the-art models for a wide range of computer vision tasks.

    To get started, we will walk you through the process of setting up Detectron2 and training your own object detection and segmentation models. We will provide code snippets and visualization techniques to help you understand the inner workings of the models and optimize their performance.

    By the end of this post, you will have a solid understanding of how to use Detectron2 to develop cutting-edge computer vision applications. So, grab your favorite IDE and let’s dive into the exciting world of computer vision with Detectron2!
    #HandsOn #Computer #Vision #Detectron2 #Develop #object #detection #segmentation #models #code #visualization #approach

  • Computer Vision and Image Processing: Fundamentals and Applications

    Computer Vision and Image Processing: Fundamentals and Applications


    Price: $170.00 – $128.52
    (as of Dec 24,2024 13:42:58 UTC – Details)



    Computer Vision and Image Processing: Fundamentals and Applications

    Computer vision and image processing are two closely related fields that have revolutionized the way we interact with technology. From facial recognition on our smartphones to autonomous vehicles, these technologies have a wide range of applications in various industries.

    Computer vision is the field of study that focuses on enabling computers to interpret and understand visual information from the real world. This involves tasks such as object detection, image classification, and image segmentation. Image processing, on the other hand, involves manipulating and enhancing visual images to improve their quality or extract useful information.

    Fundamentally, computer vision and image processing rely on algorithms and techniques that analyze and interpret visual data. This includes machine learning algorithms, neural networks, and deep learning techniques. By training these models on large datasets, computers can learn to recognize patterns and make decisions based on visual information.

    The applications of computer vision and image processing are vast and diverse. In the medical field, these technologies are used for diagnosing diseases from medical images, such as X-rays and MRIs. In the automotive industry, computer vision is crucial for enabling autonomous vehicles to navigate and detect obstacles on the road. In retail, these technologies are used for facial recognition and tracking customer behavior in stores.

    Overall, computer vision and image processing have transformed the way we interact with technology and have enabled a wide range of innovative applications. As these fields continue to advance, we can expect to see even more groundbreaking developments in the future.
    #Computer #Vision #Image #Processing #Fundamentals #Applications