IMAGE PROCESSING WITH OPENCV USING PYTHON
IMAGE PROCESSING:
Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image.
- OPENCV:
OpenCV-Python is a library of Python bindings designed to solve computer vision problems. ... All the OpenCV array structures are converted to and from Numpy arrays. This also makes it easier to integrate with other libraries that use Numpy such as SciPy and Matplotlib.
OpenCV (Open Source Computer Vision Library) is an open source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in the commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.
The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc. OpenCV has more than 47 thousand people of user community and estimated number of downloads exceeding 18 M. The library is used extensively in companies, research groups and by governmental bodies.
- python libraries used in task:
- opencv
- numpy
Lets have a look at task
?? Task 4.1
?? Create image by yourself Using Python Code
?? Task 4.2
?? Take 2 image crop some part of both image and swap it.
Images before swap:
Images after swap:
?? Task 4.3
?? Take 2 image and combine it to form single image. For example collage
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