Updated April 6, 2023
Introduction to OpenCV read image()
OpenCV read image() is an inbuilt function present in the OpenCV library in the Python programming language, which helps the system read the images provided to the system by the user. The read image array is expected to be containing data that is at the pixel level. With respect to the requirement, the user can modify the data of the image that has been provided at the pixel level. This is done by updating the values of the array at the pixel level. The function enables the system to read the image and as the output returns a three-dimensional (3D) or 2 dimensional (2D) Matrix, which is based on the number and variance of the colors (color channels) that are present in the image. It must be noted, for images that are grey-scaled or binary, a two-dimensional array suffices, but when the provided image is colored, the array needs to be 3 dimensional.
Syntax for OpenCV read image()
Following is the syntax which has to be used in order to make utilization of the function OpenCV read image():
Parameters for OpenCV read image function.
The OpenCV read image function accepts the following parameters:
|Parameter||Description of the Parameter|
|Path/to/image *||:||This parameter represents the path is selected from which to image that is to be processed by the user can be extracted for this system to read the image.|
|Flag||:||This parameter is optional. Below are the three values that are possibly taken for the image to be red depending on the quality of pixels for the source image that needs to be processed:|
|cv2.IMREAD_COLOR||:||This parameter is responsible for reading the images with RGB colours in them but do not have any transparency channel present in the image. The default value for the flag parameter is set in this mode unless a second argument it’s provided for the flag parameter while using the read image function.|
|cv2.IMREAD_UNCHANGED||:||This parameter is responsible for reading the input images that have a Gray color scheme known as the Gray images. If the primary source of the image is presumably a colored image, then in such a case, the Gray value for each of the pixels in the image is calculated by the system by averaging the optimum color channels and further the average value for each of the pixels is taken as the primary data for the array in order to read the image.|
|cv2.IMREAD_UNCHANGED||:||This parameter is responsible for reading the image as it is from the primary source of the image. In case the primary source for the image is RGB, then the system loads the image that the user has provided into array channels of Blue, Green, and Red color. In case the primary source image is of the ARGB type, then the image is loaded by the system, including the three color-based components alongside the transparency or Alpha channel.|
|Return Value||:||This method is responsible for returning an output image that is to be loaded from the file which has been specified.|
Color channel specification for OpenCV read image function
The OpenCV read image function works by decoding the source image that has been provided to the system in two assorted meat tricks, which consist of color channels data stored in the order of the color constituents that are present in the picture (Red color, Green Color, and Blue Color) and the Alpha (representing the transparency of the image) channel.
Let us understand how the image is read with the help of an example. Assume a shape is present with the matrix (400, 460, 4), then the data in the image is represented as follows:
- The color Blue Channel is represented by (:,:, 0)
- The color Green Channel is represented by (:,:, 1)
- The color Red Channel is represented by (:,:, 2)
- The Alpha or Transparency Channel is represented by (:,:, 3)
Example of OpenCV read image()
# command used to import the OpenCV library to utilize OpenCV read image function import cv2 # command used for reading an image from the disk, cv2.imread function is used img1 = cv2.imread("educba.png", cv2.IMREAD_COLOR) # Creation of a GUI window in order to display the image on the screen cv2.imshow("image", img1) # cv2.waitKey method used for holding the window on the screen # First Parameter used for holding of the screen for the milliseconds specified by the user (must be a positive integer value) cv2.waitKey(0) cv2.destroyAllWindows()
Output for Example:
Extensions that are used for OpenCV read image()
Vendor OpenCV read image function reeds the image that has to be processed for any specific procedure to be performed by the system; it does not generally consider the extension of the image file that is being processed to determine the format for the image. Rather, it is seen to be deciding the extension for the image to be based upon the file format, which has been presented in the file data respective to the image.
It is one of the most extensively used commands for processing any image file and executive any function related to image processing and detection in the Python programming language. The OpenCV read image function is essentially important cause it supports all kinds of image files (such as JPEG, PNG, TIFF) Across all available platforms, which are the most extensively used extension in which image files are saved globally. Considering 4 other formats in combination with different operating systems, the OpenCV command considers the codec present at the OS level. For such special cases, the official documentation for the read image command can be referred to.
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