Software Alternatives, Accelerators & Startups

Keras VS Segments.ai

Compare Keras VS Segments.ai and see what are their differences

Keras logo Keras

Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Segments.ai logo Segments.ai

Multi-sensor labeling platform for robotics and autonomous driving
  • Keras Landing page
    Landing page //
    2023-10-16
  • Segments.ai Homepage
    Homepage //
    2024-04-12

Segments.ai is a fast and accurate data labeling platform for multi-sensor data annotation. You can obtain segmentation labels, vector labels, and more via the intuitive labeling interfaces for images, videos, and 3D point clouds.

Build your clever annotation workflow exactly how you want, with the flexibility you need to get the job done quickly and efficiently. Segments.ai is a self-serve platform with dedicated support from our core team of engineers when you need it.

Onboard your workforce or use one of our workforce partners. Our management tools make it easy to label and review large datasets together.

Get started with a free trial today at https://segments.ai/join

Keras

Website
keras.io
Pricing URL
-
$ Details
Platforms
-
Release Date
-

Segments.ai

$ Details
freemium €800.0 / Monthly (Includes 3,600 hours/yr of labeling usage)
Platforms
AWS Azure Python TensorFlow Hugging Face 🤗
Release Date
2020 January

Keras features and specs

No features have been listed yet.

Segments.ai features and specs

  • Image Segmentation: Semantic Segmentation / Instance Segmentation / Panoptic Segmentation
  • Image Vector Labeling: Bounding Boxes / Polygons / Polylines / Keypoints
  • Point Cloud Segmentation: Semantic Segmentation / Instance Segmentation / Panoptic Segmentation
  • Point Cloud Vector Labeling: Cuboids / Polygons / Polylines / Keypoints
  • ML-powered labeling tools: SuperPixel 2.0 / Autosegment
  • Multi-sensor fusion: 2D and 3D overlay / 3D to 2D projections
  • Powerful Python SDK: Yes
  • Unlimited sized Point Clouds: Unlimited

Keras videos

3. Deep Learning Tutorial (Tensorflow2.0, Keras & Python) - Movie Review Classification

More videos:

  • Review - Movie Review Classifier in Keras | Deep Learning | Binary Classifier
  • Review - EKOR KERAS!! Review and Bike Check DARTMOOR HORNET 2018 // MTB Indonesia

Segments.ai videos

3D point cloud labeling platform for autonomous vehicles and robotics | Segments ai

Category Popularity

0-100% (relative to Keras and Segments.ai)
Data Science And Machine Learning
Data Labeling
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Image Annotation
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Keras and Segments.ai

Keras Reviews

10 Python Libraries for Computer Vision
TensorFlow and Keras are widely used libraries for machine learning, but they also offer excellent support for computer vision tasks. TensorFlow provides pre-trained models like Inception and ResNet for image classification, while Keras simplifies the process of building, training, and evaluating deep learning models.
Source: clouddevs.com
25 Python Frameworks to Master
Keras is a high-level deep-learning framework capable of running on top of TensorFlow, Theano, and CNTK. It was developed by François Chollet in 2015 and is designed to provide a simple and user-friendly interface for building and training deep learning models.
Source: kinsta.com
15 data science tools to consider using in 2021
Keras is a programming interface that enables data scientists to more easily access and use the TensorFlow machine learning platform. It's an open source deep learning API and framework written in Python that runs on top of TensorFlow and is now integrated into that platform. Keras previously supported multiple back ends but was tied exclusively to TensorFlow starting with...

Segments.ai Reviews

We have no reviews of Segments.ai yet.
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Social recommendations and mentions

Based on our record, Keras seems to be more popular. It has been mentiond 32 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.

Keras mentions (32)

  • Using Google Magika to build an AI-powered file type detector
    The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models. - Source: dev.to / 7 days ago
  • My Favorite DevTools to Build AI/ML Applications!
    As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development. - Source: dev.to / about 2 months ago
  • Getting Started with Gemma Models
    After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow. - Source: dev.to / 2 months ago
  • How popular are libraries in each technology
    Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks. - Source: dev.to / 12 months ago
  • Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
    I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them. Source: about 1 year ago
View more

Segments.ai mentions (0)

We have not tracked any mentions of Segments.ai yet. Tracking of Segments.ai recommendations started around Mar 2021.

What are some alternatives?

When comparing Keras and Segments.ai, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

Labelbox - Build computer vision products for the real world

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Universal Data Tool - Machine learning, data labeling tool, computer vision, annotate-images, classification, dataset

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Supervisely - Supervisely helps people with and without machine learning expertise to create state-of-the-art...