Скачать с ютуб Showcasing Segments.ai for segmentation labeling on Audi A2D2 dataset в хорошем качестве

Showcasing Segments.ai for segmentation labeling on Audi A2D2 dataset

Segments.ai's labeling technology makes it easy and fast to label images for semantic and instance segmentation. We've uploaded the images from Audi's A2D2 dataset (https://www.a2d2.audi/, Audi Autonomous Driving Dataset) on Segments.ai and go through a couple of random images with you. We apply full panoptic segmentation labeling and we label cars, roads, buildings, sidewalks, trees, vegetation, pedestrians, lines, etc. Most require only a couple of clicks, which is a huge difference versus manual tools or other semi-automatic tools. This technology readily works for any automotive context, and even any perception scene in general. We can finetune this technology to your use case to make it even more efficient. Applying model-assisted labeling by leveraging your models in the loop further accelerate the entire labeling pipeline (see    • In-depth tutorial of Segments.ai's mo...  ). By adding our full set of data/model curation features, computer vision engineers are able to move their prototype models quickly into fully mature models ready for real-life deployment.