This repo will be used to provide a gentle introduction to video technology, although it's aimed to software developers / engineering we want to make it easy for anyone to learn.
The idea is to introduce some video subjects with easy to understand text (at least for developers), visual element and practical examples where is possible. Also, feel free to send PRs.
An image can be thought as a 2D matrix and if we think about colors, we can extrapolate this idea seeing this image as a 3D matrix where the additional dimensions are used to provide color info.
If we chose to represent these colors using the primary colors (red, green and blue), we then can define the tree planes: the first one red, the second green and the last the blue color.
Each point in this matrix, we'll call it a pixel (picture element), will hold the intensity (usually a numeric value) of that given color. A total red color means 0 of green, 0 of blue and max of red, the pink color can be formed with (using 0 to 255 as the possible range) with Red=255, Green=192 and Blue=203.
There are much more models to represent an image with colors. We could use a indexed palette where we'd spend only a byte for each pixel instead of 3, comparing it to RGB model. In this model instead of a 3D matrix we'd use a 2D matrix, saving memory but having much less color options.
For instance, look at the first Super Mario's picture down bellow, you can see that it has a lots of red and few blue colors therefore the red color will be the one that contributes more (the brightest parts) to the final color while the blue color contribution can be mostly only seen in Mario's eyes and part of his clothes.
And each color intensity requires a certain amount of bits, this quantity is know as bit depth. Let's say we spend 8 bits (accepting values from 0 to 255) per color (plane), therefore we have a color depth of 24 (8 * 3) bits and you can also infer that we could use 2 to the power of 24 different colors.
An image has also another property such as resolution which is the number of pixels in each dimension. It is often presented as width × height, for example the 4×4 image bellow.
You can play around with image and colors using jupyter (python, numpy, matplotlib and etc).
Another property we can see while working with images or video is aspect ratio which is simple describes the proportional relationship between width and height of an image or pixel.
When people says this movie or picture is 16x9 they usually are referring to the Display Aspect Ratio (DAR) and we also can have different shapes of a pixel, we call this Pixel Aspect Ratio.
Finally we can define a video as a succession of N frames, being its frame rate or frames per second(FPS).
Make sure you have docker installed and just run ./s/start_jupyter.sh and follow the instructions on the terminal.
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