Library containing perceptual hash algorithms using the ImageSharp library
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Updated
Apr 8, 2024 - C#
Library containing perceptual hash algorithms using the ImageSharp library
Locality Sensitive Hashing, fuzzy-hash, min-hash, simhash, aHash, pHash, dHash。基于 Hash值的图片相似度、文本相似度
Remove duplicate documents/videos/images via popular algorithms such as SimHash, SpotSig, Shingling, etc.
This is a simple online shopping web application that I developed for an assignment of the bachelor's degree. For the front-end, a HTML + CSS template has been used while the backend has been developed using PHP, MYSQL, AJAX, jQuery & etc. Sharing this for the purpose of beginners to use this as reference to work on their own projects...
Finding similar images from image URLs using ImageHash
Build a computer vision-based technology to process and detect the potholes present in an image.
Merge images folders from scanlations and raws mangas, useful when the manga doesn't have an official translation
Develop and train image classification models using advanced deep learning techniques to identify diseases specific to apples.
This project provides a tool to compare two images using various similarity metrics, including histograms, structural similarity index (SSIM), mean squared error (MSE), mean absolute error (MAE), feature matching, and image hashing.
an API that extracts text from images & generates image hashes for duplicacy detection
a Python command-line tool that identifies and groups similar images using average hashing. It supports single-level and recursive directory scanning, adjustable similarity threshold, and presents results in JSON format. Ideal for image deduplication, organization, and content-based retrieval tasks.
Distributed system which runs several algorithms to flag explicit content before getting posted in social media.
Multi Server Authentication service using Bio-Hash.
A PyTorch implementation of a machine learning perceptual image hash algorithm for near-duplicate detection and fast content-based image retrieval.
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