Locally run web app and Chrome extension to remove duplicates from Google Photos
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Updated
May 30, 2024 - Python
Locally run web app and Chrome extension to remove duplicates from Google Photos
computer vision and sports
A Python toolkit for image clustering using deep learning, PCA, and K-means, with support for GPU and CPU processing. Simplify your image analysis projects with advanced embeddings, dimensionality reduction, and automated visual categorization.
Code implementation for our DAS, 2020 paper titled "Fused Text Recogniser and Deep Embeddings Improve Word Recognition and Retrieval"
Mind-X is my intelligent alter ego that understands me the best. It assists with and resolves my bothersome tasks, growing in real-time as a next-generation PersonAI system.
This app allows users to search for products by either entering text or uploading an image, and retrieves relevant products from a database
Content for workshops on image dataset curation @ HPI's AI Service Center
Text2ImageDescription retrieves relevant images from Pascal VOC 2012 dataset using OpenAI CLIP, based on text queries, and generates descriptions using quantized Mistral-7b model.
Uncover visual connections in a flash with AI-powered reverse image search.
OpenL3: Open-source deep audio and image embeddings
This repository contains the implementation of a facings identifier using YOLOv8 and image embeddings. The goal of this project is to count the number of facings (product instances) of each product present on shelves in a retail store using computer vision techniques.
end-to-end image search app
This notebook demonstates end-to-end process of generating image embeddings from Flickr8k dataset using InceptionV3 and generate captions using LSTM.
project group 129
Calculate image and document images on edge. Use these embeddings for on-edge use cases and flow them to our system for other uses.
imgs.ai is a fast, dataset-agnostic, visual search engine for digital art history based on neural network embeddings.
Code implementation for our ICPR, 2020 paper titled "Improving Word Recognition using Multiple Hypotheses and Deep Embeddings"
Hybrid recommendation engine using deep learning that incorporates user and item features, including images and text.
Kernel Fisher Discriminant Analysis implementation following https://arxiv.org/abs/1906.09436
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