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Raspberry Pi Computer Vision Programming

You're reading from   Raspberry Pi Computer Vision Programming Design and implement computer vision applications with Raspberry Pi, OpenCV, and Python 3

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781800207219
Length 306 pages
Edition 2nd Edition
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Author (1):
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Ashwin Pajankar Ashwin Pajankar
Author Profile Icon Ashwin Pajankar
Ashwin Pajankar
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Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Introduction to Computer Vision and the Raspberry Pi 2. Chapter 2: Preparing the Raspberry Pi for Computer Vision FREE CHAPTER 3. Chapter 3: Introduction to Python Programming 4. Chapter 4: Getting Started with Computer Vision 5. Chapter 5: Basics of Image Processing 6. Chapter 6: Colorspaces, Transformations, and Thresholding 7. Chapter 7: Let's Make Some Noise 8. Chapter 8: High-Pass Filters and Feature Detection 9. Chapter 9: Image Restoration, Segmentation, and Depth Maps 10. Chapter 10: Histograms, Contours, and Morphological Transformations 11. Chapter 11: Real-Life Applications of Computer Vision 12. Chapter 12: Working with Mahotas and Jupyter 13. Chapter 13: Appendix 14. Other Books You May Enjoy

Retrieving image properties

We can retrieve and use many properties, such as the data type, the dimensions, the shape, and the size of bytes of an image with NumPy. Open the Python 3 interpreter by running the python3 command in the command prompt. Then, run the following statements one by one:

>>> import cv2
>>> img = cv2.imread('/home/pi/book/dataset/4.1.01.tiff', 0)
>>> print(type(img))

The following is the output of these statements:

<class 'numpy.ndarray'>

The preceding output confirms that the OpenCV imread() function read an image and stored it in NumPy's ndarray format. The following statement prints dimensions of the image it read:

>>> print(img.ndim)
2

The image is read in grayscale mode, which is why it is a two-dimensional image. It just has a single channel composed of intensities of grayscale. Now, let's see its shape:

>>> print(img.shape)
(256, 256)

The preceding...

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