Diffgram is described as 'Operating System for Visual Deep Learning' and is an app. There are more than 10 alternatives to Diffgram for SaaS, Web-based, Self-Hosted, Mac and Windows. The best Diffgram alternative is Meta SAM 2, which is both free and Open Source. Other great apps like Diffgram are HyperLabel, Supervisely, Label Box and Heartex.
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.
A desktop application with a UX built for through-put, HyperLabel is a complete toolset for quality labeling process management and training data creation.
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.
A complete solution for your training data problem with fast labeling tools, human workforce, data management, a powerful API and automation features.
Data labeling tool for various data types with a customizable interface, annotation team management, and automatic labeling through active learning.
Deep Block is the world's fastest AI-powered remote sensing imagery analysis solution. Train your own AI models to detect instantly any objects in large satellite, aerial, and drone images. With its no-code data labeling interface, you can achieve your MLOps projects in...
A downloadable annotation tool for NLP and computer vision tasks such as named entity recognition, text classification, object detection, image segmentation, A/B evaluation and more.
The SuperAnnotate platform enables you to build, fine-tune, iterate, and manage your AI models faster, with the highest-quality training data.
Edgecase.ai offers a full suite of services and software for data annotation, synthetic data and AI services. From dedicated professionals, to medical professionals, agronomists and other sectors.
The platform for computer vision experts to iterate more quickly between data labeling, model training and failure case discovery.
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