How to convert images from AWS to OpenCV/NumPy

Today, since I need to store a large dataset and to access it like I am on my local machine, I explored AWS S3. After having created a bucket, I had a look at the official guide of boto3. The guide suggests to download the files to your local HD and then processing them. This brings to a continuous download and delete files that is not healthy for your hard drive.

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Color Quantization

In this post, we are going to talk about color quantization. Color quantization is a technique for reducing the number of used in an image and, as stated in Wikipedia “this is important for displaying images on devices that support a limited number of colors and for efficiently compressing certain kinds of images. This also leads to a less variance in the colors. In other terms, if we want that an image is made of just 5 colors, a color quantization technique analyzes the image pixel by pixel in order to fit those pixels in the range defined by the 5 colors and so, rearranging the image.

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Histogram Comparison

In the previous post, we discussed about histograms and how to equilize images, in this post we are going to talk about how to compare histograms. Histogram Comparison is one of the oldest way of comparing images in order to classify them according to a reference image. The main core idea behind this technique is to “reduce” the image to a histogram representation and compare it with other image histograms by using a metric in order to provide a rank of similarity between to images.

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