I feel like the robotics space has really been heating up recently, and part of this acceleration is because more mature tools are emerging. I've made a little market map to highlight some of the best tools for robotics developers. Which ones did I miss?

@NielsRogge and I wrote a blog post on zero-shot image segmentation for @huggingface. The blogpost shows how you can use CLIPSeg with 🤗Transformers and upload the predictions to @SegmentsAI 📰 Blog: huggingface.co/blog/clipseg-… 📒 Notebook: colab.research.google.com/gi…

Labeling point clouds for ML is very tedious & time consuming. Luckily, you can use model predictions to speed up the annotation. Check out my new guide for @SegmentsAI where I explain how to do so! ➡️ segments.ai/blog/fast-point-…

Lidar has the potential to make autonomous vehicles better & safer. I made an overview of 10 labeled lidar datasets you can use in ML projects today. Lmk if I missed any! segments.ai/blog/lidar-drivi…

In our new guide, @nielsrogge and I show how you can use @huggingface and @segmentsai to fine-tune SegFormer on your own data. We used it to build a semantic segmentation model for a pizza delivery robot🍕🤖 📰 Blog: huggingface.co/blog/fine-tun… 📒Notebook: colab.research.google.com/dr…

Shipped my first ML feature for @SegmentsAI today🚀 Autosegment makes labeling images easier by automatically creating a segmentation mask within a bounding box. Made possible by @huggingface behind the scenes🤗 Thx @NielsRogge for the useful notebooks + implementations