Keras-Cv

Visit Tool

KerasCV is an open-source library of modular computer vision components that integrates natively with TensorFlow, JAX, and PyTorch. It enables developers to build industry-strength computer vision workflows.

Claim this tool

No Views Yet

At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is keras-cv?

KerasCV is a comprehensive open-source library offering modular computer vision components designed for seamless integration with Keras 3, supporting TensorFlow, JAX, and PyTorch backends. It provides a rich collection of models, layers, metrics, and callbacks for common computer vision tasks such as data augmentation, classification, object detection, segmentation, and image generation. Developers can leverage KerasCV to quickly assemble production-grade, state-of-the-art training and inference pipelines. The library ensures the same level of polish and backward compatibility as the core Keras API, maintained by the Keras team. While KerasCV is transitioning to KerasHub for new vision model development, existing functionalities remain robust and supported.

Best used for

Ideal for developers who need to rapidly prototype and deploy computer vision solutions, integrate advanced models into existing Keras 3 workflows, and leverage multi-framework compatibility. Especially valuable for those building applications requiring robust image classification, object detection, or generative AI capabilities.

Common actions

build computer vision models

implement data augmentation

perform object detection

train image classifiers

integrate vision components

low-code/no-codeopen-sourcecollaborationdeepfakeautomated workflowworkflows"AI Agents"github copilotface swapping

Capabilities

Key features

Modular computer vision components
Multi-framework compatibility (TF, JAX, PyTorch)
Pre-trained models available
Data augmentation layers
Object detection, classification, segmentation
Image generation capabilities

Target Audience

developer

Integrations

tensorflowjaxpytorch

Pricing & Plans

Open Source

Free

FAQs

What is the future of KerasCV given its move to KerasHub?

KerasCV is transitioning new vision model development to KerasHub. Existing KerasCV functionalities will continue to work as is, and nothing will break. This move aims to consolidate and streamline the development of new computer vision models within the Keras ecosystem.

Which Keras versions are supported by KerasCV?

KerasCV supports both Keras 2 and Keras 3. For new users, Keras 3 is recommended as it enables the use of KerasCV models and layers with JAX, TensorFlow, and PyTorch, offering greater flexibility and multi-framework compatibility.

How do I configure KerasCV to use a specific backend like JAX or PyTorch?

To configure KerasCV with a specific backend (JAX, TensorFlow, or PyTorch), you need to set the KERAS_BACKEND environment variable. This must be done before importing any Keras libraries, for example, by using `export KERAS_BACKEND=jax` or `os.environ["KERAS_BACKEND"] = "jax"` in Python.

Trending

Subcategories trending in Coding & Development

Open Source & Models DevOps & Infrastructure No-Code / Low-Code Testing & QA Backend & APIs Prompt Engineering

Trending

Explore

Browse AI tools by category

Content & Design Productivity & Business Coding & Development AI Agents & Automation Research & Education Wellness & Lifestyle Career Development Marketing & Growth Data & Analytics Customer Support & CX Finance E-commerce