bilel-agrebi / image-compression

Image Compression with K-Mean Clustering #MLproject Unsupervised Technique based on 16 million colors represented as 16 colors to compress the image That involved k-means clustering with scikit-learn and Python to compress images by Creating interactive, GUI components in Jupyter notebooks using Jupyter widgets where i have used essential modules and helper functions from NumPy, Matplotlib, scikit-learn, and Jupyter Widgets. staring from #Datapreprocessing to Import images from a local directory and store them as numpy arrays. then Visualize the set of pixels from the original image as a two 2-D point clouds in color space. and Perform k-means clustering with scikit-learn's to reduce the number of possible colors in the image from over 16 million to 16 also Created an Interactive Controls with Jupyter Widgets.

Image-Compression

Image Compression with K-Mean Clustering #MLproject Unsupervised Technique based on 16 million colors represented as 16 colors to compress the image That involved k-means clustering with scikit-learn and Python to compress images by Creating interactive, GUI components in Jupyter notebooks using Jupyter widgets where i have used essential modules and helper functions from NumPy, Matplotlib, scikit-learn, and Jupyter Widgets. staring from #Datapreprocessing to Import images from a local directory and store them as numpy arrays. then Visualize the set of pixels from the original image as a two 2-D point clouds in color space. and Perform k-means clustering with scikit-learn's to reduce the number of possible colors in the image from over 16 million to 16 also Created an Interactive Controls with Jupyter Widgets.