bilel-agrebi Goto Github PK
Name: Bilel agrebi
Type: User
Bio: Master Degree Student
Name: Bilel agrebi
Type: User
Bio: Master Degree Student
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.
Compression of images with JPEG algorithm using python and Huffman codes.
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