VoTT VS make-sense

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.

Hi 👋🏻! I’m creator of https://makesense.ai. It supports Instance Segmentation. Take a look at the repo: https://github.com/SkalskiP/make-sense

I created tool called MakeSense: https://github.com/SkalskiP/make-sense it is completely free and open sourced on GH

Haven't heard of those two, but would be really awesome to see an integration. We have an open API[1] for just this reason: we really want to make it easy to use (and source) your data across all the different tools out there. We've recently launched integrations with other labeling[2] and AutoML[3] tools (and have integrations with the big-cloud AutoML tools as well[4]). We're hoping to have a bunch more integrations with other MLOps tools & platforms in 2023.

Re synthetic data specifically, we've written a couple of how-to guides for creating data from context augmentation[5], Unity Perception[6], and Stable Diffusion[7] & are talking to some others as well; it seems like a natural integration point (and someplace where we don't need to reinvent the wheel).

[1] https://docs.roboflow.com/rest-api

[2] https://github.com/SkalskiP/make-sense/pull/298

[3] https://github.com/ultralytics/yolov5/discussions/10425

[4] https://docs.roboflow.com/train/pro-third-party-training-int...

[5] https://blog.roboflow.com/how-to-create-a-synthetic-dataset-...

[6] https://blog.roboflow.com/unity-perception-synthetic-dataset...

[7] https://blog.roboflow.com/synthetic-data-with-stable-diffusi...

Two things that carried me the most are my blog https://medium.com/@skalskip - which gave me my first job in computer vision, and my open-source GitHub project: https://github.com/SkalskiP/make-sense - which gave me all my jobs since I created it.

Link to GitHub project: https://github.com/SkalskiP/make-sense

I have also looked into make-sense and currently the docker and the npm refuse to work. I have already opened a ticket describing the issue .