Label Studio is a multi-type data labeling and annotation tool with standardized output format
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Updated
Jun 3, 2024 - JavaScript
Label Studio is a multi-type data labeling and annotation tool with standardized output format
Nudity detection with JavaScript and HTMLCanvas
ML data annotations made super easy for teams. Just upload data, add your team and build training/evaluation dataset in hours.
Source code of Indian Paper Currency Classification 🔥
LabelD is a quick and easy-to-use image annotation tool, built for academics, data scientists, and software engineers to enable single track or distributed image tagging. LabelD supports both localized, in-image (multi-)tagging, as well as image categorization.
A tool for quickly training image classifiers in the browser
Chrome browser extension for using TensorFlow image recognition on web pages
Etiketai is an online tool designed to label images, useful for training AI models
A simple example on Image Classification in Node.js with TensorFlow.js
A multipurpose Discord with moderation, Image search, AI Image recognition and a music player. The bot is designed to be hosted locally on a PC or on Heroku. Feel free to contact or ask me anything by opening an issue. AI Image Recognition by IBM Watson through Watson API.
A project on making a game like Quick Draw using Machine Learning with Convolutional Neural Network.
Our powerful image search engine uses vector databases to store and search for similar images. Upload your images and use an input image to quickly identify the closest matches. With our app, you can easily organize and search your image collection with speed and accuracy. Try it today!
A Visualization Tool for Image-based Machine Learning Projects - Great for object-detection and image classification projects
Create, train and deploy AI models without writing code
Binary classification to filter and block unsolicited NSFW content from annoying coworkers... --- ...
A web mapping app to test, tweak and train the land cover classification from a deep neural network model built by @microsoft
Real-time face recognition using OpenCV, Node.js, and WebSockets.
Hack the Map 2018 Winning Entry: Easily train machine learning models using tile maps & ArcGIS.
Deteksi penyakit pada (daun) jagung berbasis citra dengan menggunakan metode GLRLM dan FCH.
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