Object Detection Systems

Driving Sophisticated Computer Vision with Machine Learning

One of the most powerful applications of machine learning and computer vision is object detection. While it is trivial for a human being to identify and locate specific objects within an image, the sheer volume of data encoded in a given image—especially one at a very high resolution—has until quite recently made computer-powered object detection very challenging. 

Today, object detection systems powered by Neural Magic’s Inference Engine can be used to develop sophisticated computer vision applications for industries and use cases ranging from industrial manufacturing to retail to media—helping companies achieve previously impossible feats, at a fraction of the cost.

 

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Run Object Detection Models on a CPU

Today, when machine learning engineers run object detection models, they often make choices that affect the quality of outcomes, because they are forced to make untenable sacrifices between:

  • Performance
  • Batch Size
  • Accuracy
  • Cost

Neural Magic addresses these limitations by generating GPU-class performance on commodity CPUs.

Software Flexibility

Bring computer vision to general-purpose CPUs. Run models anywhere: on premise, in the cloud, or at the edge.

Seamless Integration

Integrate seamlessly into existing CI/CD pipelines. Deploy in containers or virtual machines, and manage with Kubernetes like any modern software application.

Better Price Performance

High-performance algorithms can run AI on commodity machines via smarter CPU memory utilization.

Today we have support for SSD networks.

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Try Neural Magic Today

The Neural Magic Inference Engine fits seamlessly into existing CI/CD pipelines, can be deployed in containers or virtual machines, and can be managed with Kubernetes like any modern software application.

Sign up for early access