Roboflow

Wanted to validate a quick idea so I prompted our new Agent and it built this for me from scratch in 10 minutes (left and right lanes are marked from driver's pov). Three months ago, if you told me I’d be able to do this so quickly, I’d politely call you a liar. A lot of production-deployed CV work has always been plumbing between pieces. We're now at a point where that layer gets easier, and teams get more room to focus on the parts that determine whether a model performs exceptionally well in production: data quality, training configs, and deployment. more coming soon on this front ... stay tuned!

Made a quick video showing part of the workflow behind a baseball computer vision project I've been working on in my free time Driveline Baseball Enterprises, Inc. I walk through how I used Roboflow as one part of the pipeline for uploading images, organizing and versioning the dataset, and then carrying that into our own training and post-processing workflow. The point of the video isn’t really the tooling by itself, it’s more about showing how the whole process connects. Going from raw image data, to dataset management, to training, to the final visual output is something that never really gets much love. I think a lot of people only ever see the finished result, but the interesting part is how all the pieces actually tie together to make that result possible. In this case, that meant turning labeled footage into a system that could eventually play a role in our broader tech stack. Cool project to be a part of. 😎 #ComputerVision #SportsTech #BaseballTech #MachineLearning #Python #DataPipeline #MLOps #AI #Baseball

You can also run Segmentation with the full Open-source RFDETR model from Roboflow in real-time 🔥🔥 A few lines of code and you have the model running and its the best mask around the objects I have seen in such a fast model even for the Nano version. Its based on the transformer architecture so you get the awesome level of detail and also very fast inference. from rfdetr import RFDETRSegMedium model = RFDETRSegMedium() detections = model.predict(frame_rgb)

A Roboflow é uma plataforma de visão computacional que permite organizar bases de imagens, anotar objetos, treinar modelos e realizar deploy de inferência via API ou edge. Quero compartilhar nosso artigo publicado no blog da Roboflow, que apresenta um case real de automação da contagem de conídios com o uso de visão computacional. No artigo, mostramos como uma atividade manual, repetitiva e sujeita a variações foi transformada em um processo digital, padronizado e muito mais escalável, com o apoio do Roboflow e do Lovable para otimizar a rotina laboratorial e tornar a tomada de decisão mais ágil. Os resultados vão além da eficiência operacional. O case destaca ganhos em padronização, rastreabilidade, redução da subjetividade e liberação das equipes para atividades de maior valor agregado. Para profissionais que atuam com qualidade, laboratório, indústria, inovação, dados ou inteligência artificial aplicada aos negócios, a leitura é bastante recomendada. https://lnkd.in/dEwYBZFk