OpenCV with Python by example build real-world computer vision applications and develop cool demos using OpenCV for Python
Build real-world computer vision applications and develop cool demos using OpenCV for Python About This Book Learn how to apply complex visual effects to images using geometric transformations and image filters Extract features from an image and use them to develop advanced applications Build algori...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing
2015.
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| Edición: | 1st edition |
| Colección: | Community experience distilled.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629813906719 |
Tabla de Contenidos:
- Cover; Copyright; Credits; About the Author; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Applying Geometric Transformations to Images; Installing OpenCV-Python; Windows; Mac OS X; Linux (for Ubuntu); Reading, displaying, and saving images; What just happened?; Loading and saving an image; Image color spaces; Converting between color spaces; What just happened?; Image translation; What just happened?; Image rotation; What just happened?; Image scaling; What just happened?; Affine transformations; What just happened?; Projective transformations
- What just happened?Image warping; Summary; Chapter 2: Detecting Edges And Applying Image Filters; 2D convolution; Blurring; Size of the kernel versus blurriness; Edge detection; Motion blur; Under the hood; Sharpening; Understanding the pattern; Embossing; Erosion and dilation; Afterthought; Creating a vignette filter; What's happening underneath?; How do we move the focus around?; Enhancing the contrast in an image; How do we handle color images?; Summary; Chapter 3: Cartoonizing an Image; Accessing the webcam; Under the hood; Keyboard inputs; Interacting with the application; Mouse inputs
- What's happening underneath?Interacting with live video stream; How did we do it?; Cartoonizing an image; Deconstructing the code; Summary; Chapter 4: Detecting And Tracking Different Body Parts; Using Haar cascades to detect things; What are integral images?; Detecting and tracking faces; Understanding it better; Fun with faces; Under the hood; Detecting eyes; Afterthought; Fun with eyes; Positioning the sunglasses; Detecting ears; Detecting a mouth; It's time for a moustache; Detecting a nose; Detecting pupils; Deconstructing the code; Summary; Chapter 5: Extracting Features From an Image
- Why do we care about keypoints?What are keypoints?; Detecting the corners; Good Features To Track; Scale Invariant Feature Transform (SIFT); Speeded Up Robust Features (SURF); Features from Accelerated Segment Test (FAST); Binary Robust Independent Elementary Features (BRIEF); Oriented FAST and Rotated BRIEF (ORB); Summary; Chapter 6: Creating a Panoramic Image; Matching keypoint descriptors; How did we match the keypoints?; Understanding the matcher object; Drawing the matching keypoints; Creating the panoramic image; Finding the overlapping regions; Stitching the images
- What if the images are at an angle to each other?Why does it look stretched?; Summary; Chapter 7: Seam Carving; Why do we care about seam carving?; How does it work?; How do we define ""interesting""?; How do we compute the seams?; Can we expand an image?; Can we remove an object completely?; How did we do it?; Summary; Chapter 8: Detecting Shapes and Segmenting an Image; Contour analysis and shape matching; Approximating a contour; Identifying the pizza with the slice taken out; How to censor a shape?; What is image segmentation?; How does it work?; Watershed algorithm; Summary
- Chapter 9: Object Tracking
