Nvidia Jetson Nano vs. Xavier NX Object Detection Comparison

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Hardware
NVIDIA Jetson Nano. and NVIDIA Jetson Xavier NX
Software OS
NVIDIA Jetpack SDK 4.6.1
Model : SSD-Mobilenet-v2 ( TensorFlow FP32 )
Compare Performance with Jetson Inference
Jetson Inference
Instructional guide for inference and real-time DNN vision library for NVIDIA Jetson Nano/TX1/TX2/Xavier NX/AGX Xavier/AGX Orin.
This code uses NVIDIA TensorRT for efficiently deploying neural networks onto the embedded Jetson platform, improving performance and power efficiency using graph optimizations, kernel fusion, and FP16/INT8 precision.
Vision primitives, such as imageNet for image recognition, detectNet for object detection, segNet for semantic segmentation, and poseNet for pose estimation inherit from the shared tensorNet object. Examples are provided for streaming from live camera feed and processing images. See the API Reference section for detailed reference documentation of the C++ and Python libraries.
In this demo use only DetectNet.
Locating Objects with DetectNet
The previous recognition examples output class probabilities representing the entire input image. Next we're going to focus on object detection, and finding where in the frame various objects are located by extracting their bounding boxes. Unlike image classification, object detection networks are capable of detecting many different objects per frame.
The detectNet object accepts an image as input, and outputs a list of coordinates of the detected bounding boxes along with their classes and confidence values. detectNet is available to use from Python and C++. See below for various pre-trained detection models available for download. The default model used is a 91-class SSD-Mobilenet-v2 model trained on the MS COCO dataset, which achieves realtime inferencing performance on Jetson with TensorRT.
As examples of using the detectNet class, we provide sample programs for C++ and Python:
• detectnet.cpp (C++)
• detectnet.py (Python)
These samples are able to detect objects in images, videos, and camera feeds. For more info about the various types of input/output streams supported, see the Camera Streaming and Multimedia page.
Jetson Inference
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[@АндрейПавлов-д7р6м]

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