Software Alternatives & Reviews

Colorize It VS Roboflow Universe

Compare Colorize It VS Roboflow Universe and see what are their differences

Colorize It logo Colorize It

Use deep learning to colorize black and white photos

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.
  • Colorize It Landing page
    Landing page //
    2023-10-19
  • Roboflow Universe Landing page
    Landing page //
    2022-12-11

Category Popularity

0-100% (relative to Colorize It and Roboflow Universe)
Photos & Graphics
100 100%
0% 0
Developer Tools
0 0%
100% 100
Tool
100 100%
0% 0
AI
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Roboflow Universe seems to be a lot more popular than Colorize It. While we know about 18 links to Roboflow Universe, we've tracked only 1 mention of Colorize It. 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.

Colorize It mentions (1)

  • Two homeless men sit in front of the recently completed World Trade Centre in 1975. Colorized by me.
    Here is a website that allows you to upload a picture and it will do the magic. Source: about 3 years ago

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 / 9 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
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What are some alternatives?

When comparing Colorize It and Roboflow Universe, you can also consider the following products

Image Colorizer - Colorize black and white images automatically

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

Myheritage In Color - Myheritage In Color is a best-in-class technological tool that has been designed for colorizing old photos.

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

ColorSurprise AI Pixbim - ColorSurprise AI Pixbim is an effective and simple to use tool that allows you to colorize old images courtesy of having the extensive color Library.

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