cvat VS VoTT

Another powerful resource is CVAT, the Computer Vision Annotation Tool which supports both image and video annotations with advanced capabilities such as interpolation of shapes between frames, making it highly suitable for computer vision.

CVAT has an open source repo under MIT license: https://github.com/opencv/cvat I've not worked with it directly but it might be a good place to start.

ref https://github.com/opencv/cvat/issues/6061

an open source annotation tool that integrates object detectors is CVAT https://github.com/opencv/cvat however, using your own detector might require some coding. there is an integration for yolov5, but without modification it only loads the pretrained models.

This integration is currently available in the open-source version of Computer Vision Annotation Tool (http://github.com/opencv/cvat) and coming soon to CVAT.ai cloud (http://cvat.ai/)! Please use it for your computer vision projects to segment images faster.

You can download the CVAT docker from a github (Link) and install it yourself, keeping all data local. And here are two options - locally on your personal computer (or company server) or in your own cloud (there are instructions on how to do this with AWS).

In this release, CVAT introduced new features based on our vision and suggestions in the CVAT community, plus addressed more than 20+ reported bugs.

You can find more information here Waiting for your feedback here: Discord, LinkedIn, Gitter, GitHub

VoTT is an image annotation tool from Microsoft that has several interesting features that differ from the other tools. The installation of this tool is very easy because you could just simply download the installer according to your OS from their Github page.

Last app tested was this and it is safe to try, when downloaded with Safari, it shows the warnings and prevents the launch, when downloaded with Firefox it opens instantly, no warning. (I downloaded on Firefox first which launched instantly, then removed the app and tried with Safari and the warning appeared)

VoTT

I annotated 100 images which 70% was used for the training. I used 7 classes and annotated with VoTT then converted to Pytorch yolov5 from roboflow. I don't remember the mAp, sorry.

Labeling images: depending on the tool, you must label the images in PASCAL VOC format for TF or YOLO for Darknet. You can use programs like labelImg, VIA, VoTT (no longer maintain), among others.

Are you doing this as an exercise or is it that you need an image annotation tool? There are some really good open source ones, such as VoTT. Maybe you can start from there.