Understanding the PIXELS using OPENCV | Machine Learning | Beginner | Python | Image Processing смотреть онлайн

#machinelearning #python #OpenCV #ComputerVision #Numpy

What are pixels?
Pixels are the raw building blocks of an image. Every image consists of a set of pixels. There is no finer granularity than the pixel.

Normally, a pixel is considered the “color” or the “intensity” of light that appears in a given place in our image.
Most pixels are represented in two ways:

1. Grayscale/single channel
2. Color
In a grayscale image, each pixel has a value between 0 and 255, where 0 corresponds to “black” and 255 being “white.” The values between 0 and 255 are varying shades of gray, where values closer to 0 are darker and values closer 255 are lighter
Each of the three Red, Green, and Blue colors are represented by an integer in the range from 0 to 255, which indicates how “much” of the color there is. Given that the pixel value only needs to be in the range [0, 255], we normally use an 8-bit unsigned integer to represent each color intensity.
We then combine these values into an RGB tuple in the form (red, green, blue). This tuple represents our color.

Images in OpenCV are represented by NumPy arrays. To access a particular image pixel, all we need to do is pass in the (x, y)-coordinates as image[y, x]:


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