Jaykef/min-patchnizer
Minimal, clean code for video/image "patchnization" - a process commonly used in tokenizing visual data for use in a Transformer encoder.
This project helps machine learning engineers preprocess video and image data for computer vision tasks. It takes raw video files or images and transforms them into a sequence of numerically embedded 'patches,' which are then ready to be fed into a Vision Transformer model for analysis or training. This tool is designed for practitioners working with advanced deep learning models for visual understanding.
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Use this if you need to convert video or image data into a tokenized, sequence-based format suitable for Vision Transformer encoders.
Not ideal if you are looking for a general-purpose image processing library or a solution that doesn't specifically target Vision Transformer inputs.
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Python
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Last pushed
May 16, 2024
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