Similarity Libraries

15 Components & Libraries

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Similarity Libraries

Resume Matcher is an open source, free tool to improve your resume. It works by using language models to compare and rank resumes with job descriptions.

The Resume Matcher takes your resume and job descriptions as input, parses them using Python, and mimics the functionalities of an ATS, providing you with insights and suggestions to make your resume…

Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍

FAISS is a widely recognized standard for high-performance vector search engines. USearch and FAISS both employ the same HNSW algorithm, but they differ significantly in their design principles. USea…

fastdup is a powerful free tool designed to rapidly extract valuable insights from your image & video datasets. Assisting you to increase your dataset images & labels quality and reduce your data operations costs at an unparalleled scale.

🚀 Introducing VL Profiler! 🚀 We're excited to announce our new cloud product, VL Profiler. It's designed to help you gain deeper insights and enhance your productivity while using fastdup. With VL P…

A FastAPI service for semantic text search using precomputed embeddings and advanced similarity measures, with built-in support for various file types through textract.

The Swiss Army Llama is designed to facilitate and optimize the process of working with local LLMs by using FastAPI to expose convenient REST endpoints for various tasks, including obtaining text emb…

FastDup is a tool for gaining insights from a large image collection. It can find anomalies, duplicate and near duplicate images, clusters of similaritity, learn the normal behavior and temporal interactions between images. It can be used for smart subsampling of a higher quality dataset, outlier removal, novelty detection of new information to be sent for tagging. FastDup scales to millions of images running on CPU only.

FastDup is a tool for gaining insights from a large image collection. It can find anomalies, duplicate and near duplicate images, clusters of similarity, learn the normal behavior and temporal intera…

difPy - Python package for finding duplicate or similar images within folders

difPy returns various types of output that you may use depending on your use case: difPy supports the following parameters: difPy can also be invoked through the CLI by using the following commands: …

A metric for Perceptual Image-Error Assessment through Pairwise Preference (PieAPP at CVPR 2018).

In this repo, we provide the Tensorflow and PyTorch implementations of our evaluation code for PieAPP v0.1 along with the trained models. We also provide a Win64 command-line executable. The input to…

🖼️ 𝖀𝖓𝖔𝖋𝖋𝖎𝖈𝖎𝖆𝖑 PyTorch implementation of "Learning Fine-grained Image Similarity with Deep Ranking" (arXiv:1404.4661)

The goal of this project is to get hands-on experience concerning the computer vision task of image similarity. Like most tasks in this field, it's been aided by the ability of deep networks to extra…

Interactive code for image similarity using SIFT algorithm

This repo provides a working interactive code to use SIFT algorithm for image similarity. I have also presented some of the results. Check them out and let me know if you need something more. Anyone …

Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms.

Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms. Although it is not intended to have the formal rigor of a b…

Interactive Image similarity and Visual Search and Retrieval application

The AugNet Python module contains functions for the fast computation of image similarity.

In our work, we propose AugNet, a new deep learning training paradigm to learn image features from a collection of unlabeled pictures. We develop a method to construct the similarities between pictur…

Trajectory-Analysis-and-Classification-in-Python-Pandas-and-Scikit-Learn

Formed trajectories of sets of points.Experimented on finding similarities between trajectories based on DTW (Dynamic Time Warping) and LCSS (Longest Common SubSequence) algorithms.Modeled trajectories as strings based on a Grid representation.Benchmarked KNN, Random Forest, Logistic Regression classification algorithms to classify efficiently trajectories.

A university project for the postgraduate class of Data Mining. We were given a train_set with geographical points paired with the time interval. Firstly, we cleaned the dataset and then we formed t…

A python client for connecting to all the services provided by https://dandelion.eu

To detect any reasonable change in a live cctv to avoid large storage of data. Once, we notice a change, our goal would be track that object or person causing it. We would be using Computer vision concepts. Our major focus will be on Deep Learning and will try to add as many features in the process.

To detect any reasonable change in a live cctv to avoid large storage of data. Once, we notice a change, our goal would be track that object or person causing it. We would be using Computer vision co…