Apps similar to Roboflow include Supervisely, which has a free version. Other options are Datature, Amazon Rekognition, Google Cloud Vision API and Meta SAM 2. You can choose from more than 10 apps like Roboflow for the web, self-hosting and Linux.
Supervisely helps people with and without machine learning expertise to create state-of-the-art computer vision applications. We care about entire workflow from raw data to building and deploying neural networks for your special task without coding.
Datature is a Vision AI development platform that unifies data annotation, model training, and model deployment in a single interface.
Amazon Rekognition makes it easy to add deep learning-based image analysis to your applications. Search, verify, and organize millions of images. With Rekognition, you can detect objects, scenes, and faces in images. You can also search and compare faces.
United States
Cloud Vision API provides a comprehensive set of capabilities including object detection, ocr, explicit content, face, logo, and landmark detection.
SAM 2 is the first unified model for segmenting objects across images and videos. You can use a click, box, or mask as the input to select an object on any image or frame of video.
United States
Computer Vision Annotation Tool (CVAT) is a web-based tool which helps to annotate video and images for Computer Vision algorithms.
A family of foundation models producing universal features suitable for image-level visual tasks (image classification, instance retrieval, video understanding) as well as pixel-level visual tasks (depth estimation, semantic segmentation).
United States
Image annotation tool for modern computer vision. Easy to use, great for teams of all sizes. Hooks into training pipelines, designed around the latest State of the Art computer vision models.
Norway
No-code / low-code computer vision platform that uses machine learning techniches for object-detection, segmentation and OCR.
United States
No-code tool for generative image data augmentation helping to improve the accuracy of an AI model without changing the network architecture.
