Deepstream

Release notes.

View all products. Our product roadmap is defined by user feedback and we are continually developing exciting new features. Build custom supplier onboarding questionnaires and engage confidently with the right suppliers every time. Standardize your Requests, keep your communication in one place and evaluate your suppliers with ease. Save hours of negotiation time - and money - by inviting suppliers to compete online, in real-time.

Deepstream

MLPerf is an industry-standard AI performance benchmark. Today marks the release of a new set of results for MLPerf Training v3. The tasks included image classification, medical image segmentation, lightweight and heavy-weight object detection, speech recognition, language modeling, recommendation, and text to image. MLPerf Training v3. Dell Technologies submitted 30 results. These results were submitted using five different systems. The following figure shows all the convergence times for Dell systems and corresponding workloads in the benchmark. Because different benchmarks are included in the same graph, the y axis is expressed logarithmically. Overall, these numbers show an excellent time to converge for the workload in question. Figure 1. We submitted compliant results for the MLCommons Training v3. All results are stellar. They demonstrate that multinode scaling is linear and that more servers can help to solve the same problem faster. Different results allow end users to make decisions about expected performance before deploying their compute-intensive training workloads. The workloads in the submission include image classification, medical image segmentation, lightweight and heavy-weight object detection, speech recognition, language modeling, recommendation, and text to image.

MLPerf is an industry-standard AI performance benchmark.

You can even deploy them on-premises, on the edge, and in the cloud with the click of a button. There are billions of cameras and sensors worldwide, capturing an abundance of data that can be used to generate business insights, unlock process efficiencies, and improve revenue streams. DeepStream pipelines enable real-time analytics on video, image, and sensor data. Increase stream density by training, adapting, and optimizing models with TAO toolkit and deploying models with DeepStream. Developers can build seamless streaming pipelines for AI-based video, audio, and image analytics using DeepStream. DeepStream also offers some of the world's best performing real-time multi-object trackers. You can also integrate custom functions and libraries.

Download the DeepStream 6. Enter the following command:. See the Docker Containers section to learn about developing and deploying DeepStream using docker containers. See Package Contents for a list of the available files. Enter this command to see application usage:. To show labels in 2D Tiled display view, expand the source of interest with mouse left-click on the source. To return to the tiled display, right-click anywhere in the window. Keyboard selection of source is also supported. On the console where application is running, press the z key followed by the desired row index 0 to 9 , then the column index 0 to 9 to expand the source.

Deepstream

This collection serves as a hub for all DeepStream assets. Make sure you check it out! Please refer to the section below which describes the different DeepStream installers available.

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Introductory DeepStream Webinar The next version of DeepStream SDK adds a new graph execution runtime GXF that allows developers to build applications requiring tight execution control, advanced scheduling, and critical thread management. In addition, all dockerfiles are available on GitHub. Contributors 4 nv-zhliu nv-rpaliwal Rahool Paliwal nv-camilleh aparnachhajed. DeepStream is available in three different flavors of containers: Triton: Single container for both x86 and Jetson. Report repository. SDK version supported: 6. Graph Composer gives DeepStream developers a powerful, low-code development option. This enables the DeepStream community to find help at a central location. Integrate with Realtime Systems Tight scheduling control, custom schedulers and efficient resource management are a must have to integrate with deterministic systems such as robotic arms and automated quality control lines. Say goodbye to emails and excel.

You can even deploy them on-premises, on the edge, and in the cloud with the click of a button. There are billions of cameras and sensors worldwide, capturing an abundance of data that can be used to generate business insights, unlock process efficiencies, and improve revenue streams. DeepStream pipelines enable real-time analytics on video, image, and sensor data.

Branches Tags. Build custom supplier onboarding questionnaires and engage confidently with the right suppliers every time. Dismiss alert. With experience from KPMG, we provide strategic insights and best practices, so you can make the most of our platform. Contact us. From Starter to Enterprise - and even Instant Access - our plans are built for procurement teams in all organizations. Find everything you need to start developing your vision AI applications with DeepStream, including documentation, tutorials, and reference applications. To get started, download the software and review the reference audio and Automatic Speech Recognition ASR applications. Folders and files Name Name Last commit message. Getting Started with Python Learn how the latest features of DeepStream are making it easier than ever to achieve real-time performance, even for complex video AI applications.