Software Alternatives & Reviews

Roboflow Universe VS Scale Nucleus

Compare Roboflow Universe VS Scale Nucleus and see what are their differences

Roboflow Universe logo Roboflow Universe

You no longer need to collect and label images or train a ML model to add computer vision to your project.

Scale Nucleus logo Scale Nucleus

The mission control for your ML data
  • Roboflow Universe Landing page
    Landing page //
    2022-12-11
  • Scale Nucleus Landing page
    Landing page //
    2023-08-20

Roboflow Universe videos

No Roboflow Universe videos yet. You could help us improve this page by suggesting one.

+ Add video

Scale Nucleus videos

Using Scale Nucleus & Rapid to Label New Datasets Efficiently

More videos:

  • Review - Scale Nucleus: Send to Annotation
  • Review - Scale Nucleus: Find Missing Annotations

Category Popularity

0-100% (relative to Roboflow Universe and Scale Nucleus)
Developer Tools
58 58%
42% 42
AI
57 57%
43% 43
APIs
58 58%
42% 42
Software Engineering
100 100%
0% 0

User comments

Share your experience with using Roboflow Universe and Scale Nucleus. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Roboflow Universe should be more popular than Scale Nucleus. It has been mentiond 18 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Roboflow Universe mentions (18)

  • Show HN: Pip install inference, open source computer vision deployment
    It’s an easy to use inference server for computer vision models. The end result is a Docker container that serves a standardized API as a microservice that your application uses to get predictions from computer vision models (though there is also a native Python interface). It’s backed by a bunch of component pieces: * a server (so you don’t have to reimplement things like image processing & prediction... - Source: Hacker News / 8 months ago
  • Open discussion and useful links people trying to do Object Detection
    * Most of the time I find Roboflow extremely handy, I used it to merge datasets, augmentate, read tutorials and that kind of thing. Basically you just create your dataset with roboflow and focus on other aspects. Source: about 1 year ago
  • TensorFlow Datasets (TFDS): a collection of ready-to-use datasets
    For computer vision, there are 100k+ open source classification, object detection, and segmentation datasets available on Roboflow Universe: https://universe.roboflow.com. - Source: Hacker News / over 1 year ago
  • Ask HN: Who is hiring? (December 2022)
    Roboflow | Multiple Roles | Full-time (Remote) | https://roboflow.com/careers?ref=whoishiring1222 Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform[1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment. Over 100k engineers (including engineers from 2/3... - Source: Hacker News / over 1 year ago
  • Please suggest resources to learn how to work with pre-trained CV models
    Solid website and app overall for learning more about computer vision, discovering datasets, and keeping up with advancements in the field: * https://roboflow.com/learn * https://universe.roboflow.com (datasets) | https://blog.roboflow.com/computer-vision-datasets-and-apis/ * https://blog.roboflow.com. Source: over 1 year ago
View more

Scale Nucleus mentions (2)

  • [Discussion] The most painful thing about machine learning
    At Scale we built a tool for model debugging in computer vision called Nucleus (scale.com/nucleus) designed exactly for this, which is free try out if you're curious to see where your model predictions are most at odds with your ground truth. Source: over 2 years ago
  • Unit Testing for Production ML Workflows?
    To address your point about gathering edge cases, which can also be defined as cases of low model fidelity for our use cases, there is active learning and tools such as Aquarium Learning and Scale Nucleus which make it easy to implement into workflows. Source: almost 3 years ago

What are some alternatives?

When comparing Roboflow Universe and Scale Nucleus, you can also consider the following products

TensorFlow Lite - Low-latency inference of on-device ML models

Aquarium - Improve ML models by improving datasets they’re trained on

Apple Core ML - Integrate a broad variety of ML model types into your app

PerceptiLabs - A tool to build your machine learning model at warp speed.

ML Image Classifier - Quickly train custom machine learning models in your browser

Spacelift.io - Collaborative Infrastructure For Modern Software Teams