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To demonstrate the color space segmentation technique, we’ve provided a small dataset of images of clownfish in the Real Python materials repository here for you to download and play with. Remove ads Simple Segmentation Using Color Spaces Now that we understand the concept of color spaces, we can go on to use them in OpenCV. Color spaces are fully able to represent all the colors we are able to distinguish between. Color spaces, however, represent color through discrete structures (a fixed number of whole number integer values), which is acceptable since the human eye and perception are also limited. In reality, color is a continuous phenomenon, meaning that there are an infinite number of colors.
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BLACK AND WHITE FINDING NEMO FISH SOFTWARE
These color spaces are frequently used in color selection tools in software and for web design. HSV and HSL are descriptions of hue, saturation, and brightness/luminance, which are particularly useful for identifying contrast in images. They can be analyzed in HED space, a representation of the saturations of the stain types-hematoxylin, eosin, and DAB-applied to the original tissue. In certain types of medical fields, glass slides mounted with stained tissue samples are scanned and saved as images. Our printers contain ink canisters of cyan, magenta, yellow, and black. While the 0 tuple in RGB is black, in CMYK the 0 tuple is white. In the printing world, CMYK is useful because it describes the color combinations required to produce a color from a white background. There are so many color spaces because different color spaces are useful for different purposes. RGB is one of the five major color space models, each of which has many offshoots.