Nvidia Jetson Xavier multi camera Artificial Intelligence demo showcase by RidgeRun
Updated: Sep 9, 2020
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.
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.
You can also send an email to email@example.com for technical support, more information about the features, evaluation version (if available) or for details about how to sponsor a new feature.