color recognition methods(kmeans and hsv)
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Updated
May 8, 2018 - Python
color recognition methods(kmeans and hsv)
Basic scripts useful for ML operations(my goto codes for instant use)
A simple color detection virtual instrument for LabVIEW
Official Repository for the machine learning API functions deployed on zeta.ml. Built on Tensorflow and OpenCV
Virtual Drum uses openCV for detecting red color within a region and produces a drum sound.
🎨 Color recognition & classification & detection on webcam stream / on video / on single image using K-Nearest Neighbors (KNN) is trained with color histogram features by OpenCV.
Color recognition from image that uses an artificial neural network
Color recognition bot written in python
🚘 "MORE THAN VEHICLE COUNTING!" This project provides prediction for speed, color and size of the vehicles with TensorFlow Object Counting API.
Recognize color with a neural network
Color recognizer app which can detect colors from your camera using Python.
Color recognizer app which can detect names of image colors using Python.
Computer Vision and Implementations with Python
Image processing: Detect and identify different color objects in an image/video
A web app which can recognize the most prominent colours in an image and return a pie chart of those colours with their hex codes using K-means clustering algorithm.
Virtual Drum uses openCV for detecting red color within a region and produces a drum sound.
This project implements the Vehicle Color Recognition using Convolutional Neural Network. I will train it with all types of data to recognize color of anything. Not sure whether it works or not!
This is a graduation project in which I try to implement computer vision for UAV. This uses as primary factor color recognition and as secondary factor shape recognition. This is implemented using OpenCV library (Python 3.10)
This project is a real-time color detection system that can identify the color of the pixel at the center of the webcam feed. It's a simple and straightforward application to explore real-time color analysis at a pixel level.
Machine-learning behaviour, Braitenberg vehicles implementation, object- and color-recognition and message-pooling on E-Puck robots.
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