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I want to access the traefik dashboard. I have cvat setup on a server with https. I modified the docker-compose.https.yml according to the comment for using the traefik dashboard. So included the lin
A system for quickly generating training data with weak supervision
Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.
A curated list of awesome data labeling tools
GUI for marking bounded boxes of objects in images for training neural network Yolo v3 and v2
Labelbox is the fastest way to annotate data to build and ship computer vision applications.
Add a way to change the sample id output in the annotation process to a specific number (see picture).
Reason: I want to annotate large text and the app don't like it when the documents to annotate are too large, so I spitted in a sentence the document but I would like to be able to
Training Data (Data Labeling, Annotation, Workflow) for all Data Types (Image, Video, 3D, Text, Geo, Audio, more) at scale.
The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
An Integrated Experimental Platform for time series data anomaly detection.
My awesome point cloud labeling tool
A machine learning tool for automated prediction engineering. It allows you to easily structure prediction problems and generate labels for supervised learning.
Similar to #3, there can be cases where the label is not drawn/written if the coordinates are outside of the frame. In that case, the label should fallback to the regular label.
A multi-purpose Video Labeling GUI in Python with integrated SOTA detector and tracker
If you do not have any valid point cloud files in your specified pointcloud directory, you will get the error msg
labelCloud could not find any valid point cloud files inside the specified folder.
My proposal is to also print the configured path, where the software is looking for the files (e.g. "~/pointclouds").
An open source online platform for collaborative image labeling
Unity's privacy-preserving human-centric synthetic data generator
Simplest and fastest image and text annotation tool.
A cross-platform desktop image annotation tool for machine learning
NOVA is a tool for annotating and analyzing behaviours in social interactions. It supports Annotators using Machine Learning already during the coding process. Further it features both, discrete labels and continuous scores and a visuzalization of streams recorded with the SSI Framework.
Little tools to download and then weed through images, delete and classify them into groups for building deep learning image datasets (based on crawler and tkinter)
A lightweight web application for brushing labels onto time series data; useful for building training sets.
Control the quality of your labeled data with the Python tools you already know.
Use ML-Annotate to label data for machine learning purposes
A collaborative framework for annotating medical datasets using crowdsourcing.
A Super-Lightweight Annotation Tool for Experts: Label text in a terminal with just Python
Nodepool Labels operator for Kubernetes
Add a description, image, and links to the labeling topic page so that developers can more easily learn about it.
To associate your repository with the labeling topic, visit your repo's landing page and select "manage topics."
Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.
Describe the bug
When exporting a brush annotation as a PNG, the output is not mapped by the background colors specified in (Settings > Labeling Interface). In addition, when exporting as a JSON, the background colors for the attributes are not specified anywhere, leaving the values that were selected in the interface as arbitrary and as not linked to any of the outputs.
To Reproduce