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ease
features
design
support

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Description

You can develop on your laptop, then scale the same Python code elastically across hundreds or GPUs on any cloud. Ray converts existing Python concepts into the distributed setting, so any serial application can be easily parallelized with little code changes. With a strong ecosystem distributed libraries, scale compute-heavy machine learning workloads such as model serving, deep learning, and hyperparameter tuning. Scale existing workloads (e.g. Pytorch on Ray is easy to scale by using integrations. Ray Tune and Ray Serve native Ray libraries make it easier to scale the most complex machine learning workloads like hyperparameter tuning, deep learning models training, reinforcement learning, and training deep learning models. In just 10 lines of code, you can get started with distributed hyperparameter tune. Creating distributed apps is hard. Ray is an expert in distributed execution.

Description

VisionPro Deep Learning stands out as a premier software solution for image analysis driven by deep learning, specifically tailored for factory automation needs. Its robust algorithms, proven in real-world scenarios, are finely tuned for machine vision, featuring an intuitive graphical user interface that facilitates neural network training without sacrificing efficiency. This software addresses intricate challenges that traditional machine vision systems struggle to manage, delivering a level of consistency and speed that manual inspection cannot match. Additionally, when paired with VisionPro’s extensive rule-based vision libraries, automation engineers can readily select the most suitable tools for their specific tasks. VisionPro Deep Learning merges a wide-ranging machine vision toolset with sophisticated deep learning capabilities, all within a unified development and deployment environment. This integration significantly streamlines the process of creating vision applications that must adapt to variable conditions. Ultimately, VisionPro Deep Learning empowers users to enhance their automation processes while maintaining high-quality standards.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon EKS
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
MLflow
Predator MDC
Predator PDM
Predator Touch HMI
Predator Virtual CNC
PyTorch
Snowflake
TensorFlow
io.net

Integrations

Amazon EKS
Amazon Web Services (AWS)
Anyscale
Apache Airflow
Azure Kubernetes Service (AKS)
Dask
Databricks
Flyte
Google Cloud Platform
Google Kubernetes Engine (GKE)
Kubernetes
MLflow
Predator MDC
Predator PDM
Predator Touch HMI
Predator Virtual CNC
PyTorch
Snowflake
TensorFlow
io.net

Pricing Details

Free
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Anyscale

Founded

2019

Country

United States

Website

ray.io

Vendor Details

Company Name

Cognex

Founded

1981

Country

United States

Website

www.cognex.com/products/deep-learning/visionpro-deep-learning

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Alternatives

Alternatives