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AN INTRODUCTION TO DEEPSTREAM SDK Kaustubh Purandare March 2018 - PowerPoint PPT Presentation

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AN INTRODUCTION TO DEEPSTREAM SDK Kaustubh Purandare March 2018 AGENDA Introduction to DeepStream SDK DeepStream SDK Basic Building Blocks Setup & Installation Application Examples Performance Analysis 3 rd

  1. AN INTRODUCTION TO DEEPSTREAM SDK Kaustubh Purandare March 2018

  2. AGENDA Introduction to DeepStream SDK • DeepStream SDK Basic Building Blocks • • Setup & Installation Application Examples • • Performance Analysis 3 rd Party Integration • Q&A • NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 2

  3. WHAT IS DEEPSTREAM SDK 1) NVIDIA DeepStream simplifies the development of scalable intelligent video analytics (IVA) applications 2) Developers can now use this to quickly build new applications to transform video into valuable insight. 3) Applications for the DeepStream SDK include image classification, scene understanding, video categorization, content filtering etc.. NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 3

  4. DEEPSTREAM SDK FOR INTELLIGENT VIDEO ANALYTICS Access control Public Transit Parking Management Traffic Engineering Retail Analytics Securing Critical Infrastructure In-Vehicle Analytics Law Enforcement NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 4

  5. DEEPSTREAM SDK Intelligent Retail Access Smart Law traffic analytics & control parking enforcemen systems checkout t User Applications Modular, 3 rd party Sample Solution Development Scalable, DNNs & application adaptation Tools Architecture plug-ins guide plugins DeepStream SDK TensorRT Multi-stream Encode & Image capture & cuDNN Decode processing Deep Learning Multimedia Imaging Linux, CUDA NVIDIA Platforms NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 5 * Early release and limited availability.

  6. DEEPSTREAM SDK BUILDING BLOCKS NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 6

  7. SETUP & INSTALLATION A] Jetson 1) Latest JetPack https://developer.nvidia.com/embedded/jetpack 2) DeepStream on Tegra SDK https://developer.nvidia.com/deepstream-jetson 3) Ubuntu 16.04 64-bit operating system (host) 4) Jetson TX1 / TX2 Development Platform B] Running the Sample Application nvgstiva-app -c <HOME_dir>/configs/<Config.txt> \ -i /home/nvidia/<path_to_input_stream> NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 7

  8. SAMPLE APPLICATION License plate recognition (3 rd party plugin) Consolidating unique ID Metadata export Car make Display/ OSD APIs (TensorRT) Primary detection Image capture and plugin process plugin (TensorRT) Car type (TensorRT) Smart storage Car color Tracking plugin (TensorRT) Situational awareness - Identify cars, pedestrians, and two-wheelers • • Classify Make (Mercedes, BMW, Audi, …) • Classify Type (SUV, Sedan, Truck, …) • Identify Color (Black, Blue, …) • Read license plate NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 8

  9. NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 9

  10. APPLICATION FLOW Parse application configuration file Create graphs (add/don’t add elements, set properties based on configuration) Loop Set application graphs to playing Metadata generated Callback (Called per frame with metadata Overlay Graphics Callback Destroy graphs generated by the graphs – object co- (Overlay custom text / graphics per (Free up resource) ordinates, secondary labels, unique frame) tracking id, etc) NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 10

  11. CONFIGURATION FILE • Organized as groups and key- value pairs • Groups for graphs stages • Key-value pair to configure each stage • Very high granularity for configuring each stage NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 11

  12. APPLICATION FLOW Parse application configuration file Create graphs (add/don’t add elements, set properties based on configuration) Loop Set application graphs to playing Metadata generated Callback (Called per frame with metadata Overlay Graphics Callback Destroy graphs generated by the graphs – object co- (Overlay custom text / graphics per (Free up resource) ordinates, secondary labels, unique frame) tracking id, etc) NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 12

  13. GRAPHS CREATED NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 13

  14. APPLICATION FLOW Parse application configuration file Create graphs (add/don’t add elements, set properties based on configuration) Loop Set application graphs to playing Metadata generated Callback (Called per frame with metadata Destroy graphs Graphics Overlay generated by the graphs – object co- (Free up resource) (Overlay custom text / graphics per ordinates, secondary labels, unique frame) tracking id, etc) NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 14

  15. CREATING SIMPLE GRAPHSS 1) Gstreamer provides powerful tool like gst-launch to create trial / experimental graphs as per use cases. 2) File stream with Primary object detection and OnScreen Display • gst-launch-1.0 uridecodebin uri=file:///home/nvidia/video.mp4 ! nvinfer <primary-infer-properties> ! queue ! nvosd <osd- properties> ! nveglglessink 3) RTSP stream with primary object detection + tracking + secondary classification labels + OnScreen Display • gst-launch-1.0 uridecodebin uri=rtsp://10.24.1.1/video0 ! nvinfer <primary-infer-properties> ! queue ! nvtracker ! queue ! nvinfer <secondary-infer-properties> ! queue ! nvosd <osd-properties> ! nveglglessink NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 15

  16. PERFORMANCE ANALYSIS NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 16

  17. APPLICATION SOFTWARE STACK Applications ISV/ 3 rd party solutions Sample DL Networks Custom DL Networks Plugin based compute Graph ● Gstreamer Framework DeepStream Image capture & TensorRT Multistream processing cuDNN Encode & Decode Deep Learning Multimedia Imaging Linux, CUDA NVIDIA Platforms NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 17

  18. START DEVELOPING WITH DEEPSTREAM DeepStream Early Access program . Explore Metropolis . Intelligent Video Analytics Forums NVIDIA CONFIDENTIAL. DO NOT DISTRIBUTE. 18

  19. THANK YOU 19

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