Image segementation can be done using various filters in Deep Learning. One of the filter is used here to extract the most dominant colors of the image
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Updated
Nov 20, 2022 - Python
Image segementation can be done using various filters in Deep Learning. One of the filter is used here to extract the most dominant colors of the image
Web app that helps you extract colour palette from an image.
K-Means Clustering algorithm implementation to extract dominant palette colors in a picture and a new picture is formed, which is built from its predominant shading palettes. A picture contains high intensities of hues, these hues are grouped, and the generated pictures contains only extracted colors
Contains deep learning projects
A library that chooses the best colors from a picture.
Facebook Bot that posts pictures and their most vibrant colors
The Dominant Color Extractor is a simple Python application that allows you to extract the dominant color from an image file. It provides a user-friendly graphical interface built with CustomTkinter, making it easy for anyone to use.
알약 검출을 위한 주요 알고리즘을 개발하고 실험하는 레포지토리
K-Means Color extraction, Segmentation, Comparison
Compress every frame of a movie in a single color barcode. Transform entire movies into stunning single-barcode visualizations. Capture the essence of cinematic storytelling through dominant color extraction from each frame.
This repo has a Jupyter Notebook for an e-commerce NLP and data manipulation technical test.
A simple and efficient PHP function that allows you to quickly and easily determine the average color of an image.
A command-line tool for extracting dominant colors from an image.
Expose node-vibrant image analysis results via JSON API
library to extract color palettes from images - based on SkiaSharp
Heterogeneous libraries integrator for image color extraction and naming
Processing image captured in UGV or UAV navigation
🎨 Extract prominent color palette from your image automatically.
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