VoTT VS albumentations

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.

You can use albumentations if you are comfortable with using open source libraries https://github.com/albumentations-team/albumentations

One of the members of the core team of our open-source library https://albumentations.ai/

It was not the only reason he was hired; it was a solid addition to his already good performance at the interviews.

Or at least that is what the hiring manager later said.

I am one of the creators and maintainers of https://albumentations.ai/.

- 12800+ stars

Is something planned to support data augmentations? Something like https://albumentations.ai/

Here you go: https://albumentations.ai/

I think they should use some data augmentation techniques like I am using for Infinity AI if you wanna see more here. Note that most of these do not work for image generation.

Our second approach was a more automated one. Here the idea was to try out an image augmentation library, Albumentations, and use it for adversarial attacks. This time, instead of one-shot images, we applied the transformations at random time ranges. We chose for these transformations also to be more subtle than then one-shot images, such as vertical flips, grayscaling, downscaling, …

Check out albumentations. If your use case is segmentation, check out the offline augmentation of this project

I think this is the most popular open source project: https://github.com/albumentations-team/albumentations

You can also curate your own dataset by using open source images (https://universe.roboflow.com/search?q=faces%20images%3E1000) and open source augmentations (https://github.com/albumentations-team/albumentations). Or you can do use the augmentation UI (https://docs.roboflow.com/image-transformations/image-augmentation) to apply noise, blurring, shear, crop, etc.