OpenCV  4.10.0-dev
Open Source Computer Vision
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Getting Started with Images

Prev Tutorial: Building OpenCV for Tegra with CUDA
Next Tutorial: Writing documentation for OpenCV

Original author Ana Huamán
Compatibility OpenCV >= 3.4.4
Warning
This tutorial can contain obsolete information.

Goal

In this tutorial you will learn how to:

Source Code

Explanation

Now, let's analyze the main code. As a first step, we read the image "starry_night.jpg" from the OpenCV samples. In order to do so, a call to the cv::imread function loads the image using the file path specified by the first argument. The second argument is optional and specifies the format in which we want the image. This may be:

  • IMREAD_COLOR loads the image in the BGR 8-bit format. This is the default that is used here.
  • IMREAD_UNCHANGED loads the image as is (including the alpha channel if present)
  • IMREAD_GRAYSCALE loads the image as an intensity one

After reading in the image data will be stored in a cv::Mat object.

Note
OpenCV offers support for the image formats Windows bitmap (bmp), portable image formats (pbm, pgm, ppm) and Sun raster (sr, ras). With help of plugins (you need to specify to use them if you build yourself the library, nevertheless in the packages we ship present by default) you may also load image formats like JPEG (jpeg, jpg, jpe), JPEG 2000 (jp2 - codenamed in the CMake as Jasper), TIFF files (tiff, tif) and portable network graphics (png). Furthermore, OpenEXR is also a possibility.

Afterwards, a check is executed, if the image was loaded correctly.

Then, the image is shown using a call to the cv::imshow function. The first argument is the title of the window and the second argument is the cv::Mat object that will be shown.

Because we want our window to be displayed until the user presses a key (otherwise the program would end far too quickly), we use the cv::waitKey function whose only parameter is just how long should it wait for a user input (measured in milliseconds). Zero means to wait forever. The return value is the key that was pressed.

In the end, the image is written to a file if the pressed key was the "s"-key. For this the cv::imwrite function is called that has the file path and the cv::Mat object as an argument.