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Haskell Data Analysis cookbook

You're reading from   Haskell Data Analysis cookbook Explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

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Product type Paperback
Published in Jun 2014
Publisher
ISBN-13 9781783286331
Length 334 pages
Edition 1st Edition
Languages
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Author (1):
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Nishant Shukla Nishant Shukla
Author Profile Icon Nishant Shukla
Nishant Shukla
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Toc

Table of Contents (14) Chapters Close

Preface 1. The Hunt for Data FREE CHAPTER 2. Integrity and Inspection 3. The Science of Words 4. Data Hashing 5. The Dance with Trees 6. Graph Fundamentals 7. Statistics and Analysis 8. Clustering and Classification 9. Parallel and Concurrent Design 10. Real-time Data 11. Visualizing Data 12. Exporting and Presenting Index

Detecting faces and eyes through a camera stream

The camera is another source for real-time data. As frames come and go, we can perform powerful analysis using the OpenCV library.

In this recipe, we conduct facial detection through a live camera stream.

Getting ready

Install the OpenCV, SDL, and FTGL libraries for image manipulation and computer vision:

sudo apt-get install libopencv-dev libsdl1.2-dev ftgl-dev

Install an OpenCV library using cabal:

cabal install cv-combinators

How to do it…

Create a new source file, Main.hs, and follow these steps:

  1. Import the relevant libraries:
    import AI.CV.ImageProcessors
    import qualified AI.CV.OpenCV.CV as CV
    import qualified Control.Processor as Processor
    import Control.Processor ((--<))
    import AI.CV.OpenCV.Types (PImage)
    import AI.CV.OpenCV.CxCore (CvRect(..), CvSize(..))
    import Prelude hiding (id)
    import Control.Arrow ((&&&), (***))
    import Control.Category ((>>>), id)
  2. Define the source of the camera stream. We will be using the...
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