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related to: roboflowRoboflow is powerful, but confusing. Nyckel is the easy-to-use ML alternative. For most classification use cases, Roboflow is too confusing. Use Nyckel instead.
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Use Roboflow scalably and securely. Enterprise-grade infrastructure and compliance. Compliant with SOC2 Type 2 requirements; All data is encrypted in transit and at rest, with SSL transport receiving a grade A+ rating from Qualys
Even if you're not a machine learning expert, you can use Roboflow train a custom, state-of-the-art computer vision model on your own data.
Explore these datasets, models, and more on Roboflow Universe. 350+ Million Images 500,000+ Datasets 100,000+ Pre-Trained Models
Mar 16, 2023 · Once you drop the screw-dataset folder into Roboflow, the images and annotations are processed for you to see them overlayed.. If any of your annotations have errors, Roboflow alerts you. For example, if some of the annotations improperly extended beyond the frame of an image, Roboflow intelligently crops the edge of the annotation to line up with the edge of the image and drops erroneous ...
Roboflow is a computer vision platform offering tools for model training, dataset annotation, and deployment services.
Roboflow offers a collection of 119 repositories on GitHub, providing users with streamlined computer vision solutions.
Jul 30, 2021 · We've seen tremendous interest in Roboflow from the research community. Faculty and students from institutions ranging from California to Malta to Taiwan have been using Roboflow to accelerate their computer vision work.
Yes. No credit card is required to use Roboflow. For individuals with personal projects, school assignments, or research projects, Roboflow offers the Public plan to encourage exploration of computer vision.
Introducing Roboflow 100: A New Object Detection Benchmark Advancing SOTA in object recognition with a new way to benchmark CV models on real-world datasets across domains.
Roboflow Inference is an open-source platform designed to simplify the deployment of computer vision models. It enables developers to perform object detection, classification, and instance segmentation and utilize foundation models like CLIP, Segment Anything, and YOLO-World through a Python-native package, a self-hosted inference server, or a fully managed API.
