NVIDIA Jetson Xavier Multi-Camera Artificial Intelligence Demo from RidgeRun

Jetson Xavier Multi-Camera Artificial Intelligence Demo from RidgeRun

This demo from RidgeRun shows the capabilities of the Jetson Xavier by performing :

• Multi-camera capture through FPD-LINK III with Virtual Channels support,
• Display of each individual camera stream on a grid, 
• Application of CUDA video processing filters, classification and detection inference, 
• Video stabilization processing and video streaming through the network.

Please watch Jetson Xavier Multicamera + AI + Video Stabilization + CUDA Video Processing FIlters demo from RidgeRun :

Demo components:

D3 Engineering-Nvidia-Xavier FPD-Link III interface card

                                   

D3 Engineering-D3RCM-OV10640-953 Rugged Camera Module

The 8 camera streams are downscaled to 480x480 resolution and displayed on a grid. Following are the extra processing is applied to different camera streams:

Camera_1: No extra processing, just normal camera stream. Intended to be used as a point of comparison against the streams with CUDA video processing filters.

Camera_2: Sobel in X-axis CUDA video filter applied with GstCUDA plugin.

Camera_3: Border Enhancement CUDA video filter applied with GstCUDA plugin.

Camera_4: Grayscale CUDA video filter applied with GstCUDA plugin.

Camera_5: No extra processing, just normal camera stream. Intended to be used as a point of comparison against the stream with video stabilization processing.

Camera_6: Video stabilization processing applied with GstNvStabilize plugin. 

Camera_7: InceptionV1 Classification Inference applied with GstInference plugin using GPU accelerated TensorFlow.

Camera_8: TinyYoloV2 Detection Inference applied with GstInference plugin using GPU accelerated TensorFlow.

One individual camera stream selected by the user from the demo menu is streamed to the network using the GstWebRTC plugin and an OpenWebRTC application.

Demo setup, demo features in detail, demo code and performance profiling information are explained in this RidgeRun & D3 Engineering - Nvidia Partner Showcase : Jetson Xavier Multi-Camera AI Demo RidgeRun Developer Wiki.

Contact Us

Please visit our Main Website for the RidgeRun online store or Contact Us for pricing information of the engineering support, product and services.                                                                              

You can also send an email to support@ridgerun.com for a technical support, more information about the features, evaluation version (if available) or for a details about how to sponsor a new feature.

Nvidia Jetson Xavier multi camera Artificial Intelligence demo showcase by RidgeRun

This demo from RidgeRun shows the capabilities of the Jetson Xavier by performing :

• Multi-camera capture through FPD-LINK III with Virtual Channels support, 
• Display of each individual camera stream on a grid, 
• Application of CUDA video processing filters, classification and detection inference, 
• Video stabilization processing and video streaming through the network.

RidgeRun demo screen:

RidgeRun & D3 Engineering Nvidia Partner Showcase Jetson Xavier Multi-Camera AI Demo.

Demo components:

D3 Engineering-Nvidia-Xavier FPD-Link III interface card

                                   

D3 Engineering-D3RCM-OV10640-953 Rugged Camera Module

The 8 camera streams are downscaled to 480x480 resolution and displayed on a grid. Following are the extra processing is applied to different camera streams:

Camera_1: No extra processing, just normal camera stream. Intended to be used as a point of comparison against the streams with CUDA video processing filters.

Camera_2: Sobel in X-axis CUDA video filter applied with GstCUDA plugin.

Camera_3: Border Enhancement CUDA video filter applied with GstCUDA plugin.

Camera_4: Grayscale CUDA video filter applied with GstCUDA plugin.

Camera_5: No extra processing, just normal camera stream. Intended to be used as a point of comparison against the stream with video stabilization processing.

Camera_6: Video stabilization processing applied with GstNvStabilize plugin. 

Camera_7: InceptionV1 Classification Inference applied with GstInference plugin using GPU accelerated TensorFlow.

Camera_8: TinyYoloV2 Detection Inference applied with GstInference plugin using GPU accelerated TensorFlow.

One individual camera stream selected by the user from the demo menu is streamed to the network using the GstWebRTC plugin and an OpenWebRTC application.

Demo setup, demo features in detail, demo code and performance profiling information are explained in this RidgeRun & D3 Engineering - Nvidia Partner Showcase : Jetson Xavier Multi-Camera AI Demo RidgeRun Developer Wiki.

Contact Us

Please visit our Main Website for the RidgeRun online store or Contact Us for pricing information of the engineering support, product and services.                                                                              

You can also send an email to support@ridgerun.com for a technical support, more information about the features, evaluation version (if available) or for a details about how to sponsor a new feature.

RidgeRun supporting The 2019 FIRST® Robotics by providing NVIDIA Jetson support

RidgeRun love helping academic projects! RidgeRun is proud to help the teams on FIRST Robotics Competition [1] with software for embedded systems to improve the acquisition, processing and analysis of Audio and Video signals!

[1] https://www.firstinspires.org/robotics/frc

Michael, Amanda, and Emily (in the pic below) of FIRST Robotics Competition Team 102, The Gearheads, from Somerville High School in NJ, investigate the NVIDIA Jetson technology from RidgeRun.  They hope that the combination of Nvidia TX1, Auvidea J90LC, and drivers from RidgeRun will provide a cost effective, state of the art Computer Vision solution for the 2019 season. Go Gearheads!’

RidgeRun help getting the kernel built with the IMX219 V4L2 driver for TX1 on the Auvidea J90-LC for state of the art Computer Vision solution for The 2019 FIRST® 2019 season.

Watch out! and we will keep updating as the Competition progress.

For more information please contact us at support@ridgerun.com or for purchase related questions post your inquiry at our Contact Us page.