106 results for “topic:labelling”
Inference Code for Polygon-RNN++ (CVPR 2018)
PyTorch training/tool code for Polygon-RNN++ (CVPR 2018)
Open Source Data Annotation & Labeling Tools
Computer vision based ML training data generation tool :rocket:
RectLabel is an offline image annotation tool for object detection and segmentation.
VisioFirm: Cross-Platform AI-assisted Annotation Tool for Computer Vision
Video Annotation Tool
Repository for automatic classification and labeling of Urban PointClouds using data fusion and region growing techniques.
:fire: One of the most comprehensive open-source data annotation platform.
🤖 A Github bot to automatically label PRs, issues and perform all the boring operations that you don't want to do.
A demo to test Custom Labels with models trained by Amazon Rekognition
An interactive dashboard for visualisation, integration and classification of data using Active Learning.
A collaborative tool for labeling image data for yolo
PyTorch code for Deep Extreme Level Set Evolution (CVPR 2019)
A pre labelled dataset for ui element / layout detection
Topic Inference with Zeroshot models
Animal Detection in Man-made Environments using Deep Learning
A python package for interaction with time series data.
Use this tool to label forms, bounding boxes, and assigning types to annotations
A YOLO annotator, for human beings
Ml-Cli is a command line and local tool that aims to automate ML testing and provide annotation tools
Annotation Tool for Instance Segmentation of Grid Structures
Automatic Labelling for Omnivore on AWS
This is a labeling tool for Challenging Events for Person Detection from Overhead Fisheye Images (CEPDOF) fisheye dataset.
📖 UI/UX context detection engine
The FAST ROI library is useful for quickly extracting the coordinates of a rotating rectangular ROI
🥇 A versatile image labelling toolchain for deep learning.
OXI is an user-friendly graphical tool for labeling multivariate time series data
No description provided.
Helper scripts to split a large audio file into smaller chunks and annotate these chunks