Popular GitHub Repositories for Emoji Labels

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Laminar - open-source all-in-one platform for engineering AI products. Crate data flywheel for you AI app. Traces, Evals, Datasets, Labels. YC S24.

Simple project to detect objects and display 3D labels above them in AR. This serves as a basic Template for an ARKit project to use CoreML.

SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

A Light CNN for Deep Face Representation with Noisy Labels, TIFS 2018

Curated list of open source tooling for data-centric AI on unstructured data.

Official repository for the paper "High-Resolution Daytime Translation Without Domain Labels" (CVPR2020, Oral)

A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.

[CVPR'22 & IJCV'24] Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels & Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

? A voice chatbot that can imitate your expression. OpenCV+Dlib+Live2D+Moments Recorder+Turing Robot+Iflytek IAT+Iflytek TTS

A collection of 3 lambda functions that are invoked by Amazon S3 or Amazon API Gateway to analyze uploaded images with Amazon Rekognition and save picture labels to ElasticSearch (written in Kotlin)

TweetNLP for all the NLP enthusiasts working on Twitter! The Python library tweetnlp provides a collection of useful tools to analyze/understand tweets such as sentiment analysis, emoji prediction, and named entity recognition, powered by state-of-the-art language models specialised on Twitter.

Code For The Issue Label Bot, an App that automatically labels issues using machine learning, available on the GitHub Marketplace. This is also code for the blog article: "How to automate tasks on GitHub with machine learning for fun and profit"

DiffSeg is an unsupervised zero-shot segmentation method using attention information from a stable-diffusion model. This repo implements the main DiffSeg algorithm and additionally includes an experimental feature to add semantic labels to the masks based on a generated caption.

[ECCV'22] Official repository of paper titled "Class-agnostic Object Detection with Multi-modal Transformer".

Synthetic Image generation with Flip. Generate thousands of new 2D images from a small batch of objects and backgrounds.

Official Implementation of Early-Learning Regularization Prevents Memorization of Noisy Labels

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

Labelling platform for text using weak supervision.