OpenCV (Open Source Computer Vision) is a library of programming functions mainly aimed at real-time computer vision. This is cross-platform library, it provides functions that are used in multiple languages.
Coming to image processing, OpenCV enables us to perform multiple operations on image, but in order to do that we need to read an image file as input, then we can perform the desired operation and we can save it.
Let’s see a simple operation to read the image file using OpenCV library and then save it.
Functions used :
-> imread(Location_of_image, integer): The second parameter is an integer for changing the color of image. -1 To read image Unchanged and 0 To read image in gray scale.
-> imwrite(Name_after_save, variable_containing_read_image)
->waitKey(0): After execution will keep the window open till a key is pressed
-> destroyAllWindow(): It will close all the windows that were opened during the program run.
Below is the Python implementation:
- OpenCV Python Program to blur an image
- OpenCV Python Program to analyze an image using Histogram
- Python Program to detect the edges of an image using OpenCV | Sobel edge detection method
- Reading an image in OpenCV using Python
- Cartooning an Image using OpenCV - Python
- OpenCV C++ Program to blur an image
- Python | Detect corner of an image using OpenCV
- OpenCV C++ Program to create a single colored blank image
- Python | Program to extract frames using OpenCV
- Opencv Python program for Face Detection
- Image Processing using OpenCV in Java | Set 14 ( Sharpness Enhancement )
- Image Processing using OpenCV in Java | Set 13 (Brightness Enhancement)
- OpenCV Python program for Vehicle detection in a Video frame
- Image Processing in Java | Set 1 (Read and Write)
- Getting started with Scikit-image: image processing in Python
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