Photomosaic — it is an image, broken down into a grid of rectangles, each of which is replaced by a different image that suits the purpose (the image you ultimately want to display in this photo). In other words, if you look at the mosaic from a distance, you will see an image of the target; but if you get closer, you can see that the image is actually made up of many small images. This works because of the way the human eye works.
There are two kinds of mosaics, depending on how the matching is done. In a simpler form, each portion of the target image is averaged to one color. Each of the images in the library is also reduced to one color. Each part of the target image is then replaced with one part from the library where the colors are as similar as possible. Essentially, the target image is downsampled (downsampled) and then each of the resulting pixels is replaced with an image whose average color corresponds to that pixel.
In a more advanced form of photographic mosaic, the target image is not downsampled. and matching is performed by comparing each pixel in the rectangle with a corresponding pixel from each library image. The rectangle in the target is then replaced with the library image, which minimizes the overall difference. This is much more computationally intensive than the simple type, but the results can be much better as the pixel-by-pixel matching can preserve the resolution of the target image.
How do I create a photo mosaic? p >
Tiling images p>
Now let`s see how to calculate coordinates for one tile from this grid. A tile with index (i, j) has an upper left corner coordinate (i * w, i * j) and a lower right corner coordinate ((i + 1) * w, (j + 1) * h), where w and h denote the width and height of the tiles, respectively. They can be used with PIL to crop and tile this image.
Averaging color values
Every pixel in an image has a color that can be represented its values for red, green and blue. In this case, you are using 8-bit images, so each of these components has an 8-bit value in the range [0, 255]. For an image with a total of N pixels, the average RGB value is calculated as follows:
For each tile in the target image, you need to find the matching image from the images in the user-specified input folder. Use RGB averages to determine if two images are the same. The closest match is the image with the nearest RGB mean.
The easiest way to do this is — calculate the distance between RGB values in a pixel to find the best match among the input images. You can use the following distance calculation for 3D points from geometry:
Now let`s try to code this
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