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Author: alisharify7

00-opencv/readme.md

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+Computer Vision
+Computer vision is a process by which we can understand the images and videos how they are stored and how we can manipulate and retrieve data from them. Computer Vision is the base or mostly used for Artificial Intelligence. Computer-Vision is playing a major role in self-driving cars, robotics as well as in photo correction apps. 
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+OpenCV
+OpenCV is the huge open-source library for the computer vision, machine learning, and image processing and now it plays a major role in real-time operation which is very important in today’s systems. By using it, one can process images and videos to identify objects, faces, or even handwriting of a human. When it integrated with various libraries, such as NumPy, python is capable of processing the OpenCV array structure for analysis. To Identify image pattern and its various features we use vector space and perform mathematical operations on these features. 
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+The first OpenCV version was 1.0. OpenCV is released under a BSD license and hence it’s free for both academic and commercial use. It has C++, C, Python and Java interfaces and supports Windows, Linux, Mac OS, iOS and Android. When OpenCV was designed the main focus was real-time applications for computational efficiency. All things are written in optimized C/C++ to take advantage of multi-core processing. 
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+https://docs.opencv.org/4.x/da/df6/tutorial_py_table_of_contents_setup.html
+https://www.geeksforgeeks.org/opencv-overview/
+https://github.com/opencv/opencv

01-reading-image/Media/1.jpg

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+"""
+by default open cv reads images in BGR mode BLUE, GREEN, RED
+but otherlibraries cannot show this values properly like matplotlib
+so its better to convert this values to BGR before showing it in other libraries
+
+read about color spaces:
+https://www.geeksforgeeks.org/color-spaces-in-opencv-python/
+
+"""
+
+import cv2 as cv
+
+
+filename = "./Media/1.jpg" 
+
+image = cv.imread(filename, 1) # filename: str, flags: int
+# flags
+# 1   0   -1
+
+# convert BGR to RGB
+image = cv.cvtColor(image, cv.COLOR_BGR2RGB) # src, code
+
+
+# showing image with opencv
+cv.imshow("Open Cv", image) # winname: str, mat: cv2.typing.MatLik
+
+
+cv.waitKey(1000) # delay: int => milliseconds 
+# if 0 is passed its wait until a key pressed on the keyboard
+
+cv.destroyAllWindows() # remove all windows from memory
+
+
+# showing images with mathplotlib
+import matplotlib.pyplot as plt
+
+plt.imshow(image)
+plt.title("matplotlib")
+plt.waitforbuttonpress()
+plt.close('all')