/Alturos.ImageAnnotation

A collaborative tool for labeling image data for yolo

Primary LanguageC#MIT LicenseMIT

Alturos.ImageAnnotation

Alturos.ImageAnnotation

The purpose of this project is to manage training data for Neural Networks. The images are stored in an object storage for example Amazon S3. In our case we have image data for different runs that we want to annotate together. You can upload a folder into a package. For every package you can set your own tags... this information is stored in a database for example Amazon DynamoDB.

object detection result

Features

  • Collaborative annotation of images
  • Verification of image annotation data
  • Export for yolo (train.txt, test.txt, obj.names) with filters
  • No requirement for a custom server

Installation

You have the choice to use AWS or install your own environment.

Keyboard Shortcuts

Shortcut Description
Next image
Previous image
Next Object Class
Previous Object Class
0-9 Select Object Class
WASD
+Shift
+Ctrl
+Alt
Move Bounding Box
Resize
Quick
Invert

Data preperation

How many images are required

You should preferably have 2000 different images for each class or more.

Extract images from a video

If you have a video file and need the individual frames you can use ffmpeg to extract the images. This command exports every 10th frame in the video. ffmpeg -i input.mp4 -vf "select=not(mod(n\,10))" -vsync vfr 1_every_10/img_%03d.jpg

Articles of interest

Credits

This program uses icons from the Silk icon set created by Mark James, which can be found here. The icon set is licensed under a CC BY 3.0 license. Some changes were made to the icons.

Other Image Annotation Tools

List of annotation tools for machine learning research