Nvidia Jetson Model Zoo

This tutorial shows how to install mxnet v1 6 with jetson support and gluoncv on a jetson module and deploy a pre trained gluoncv model for object detection.

Nvidia jetson model zoo. Note that many other models are able to run natively on jetson by using the machine learning frameworks like those listed above. Triton allows you to use the tensorflow graphdef file directly. I d post an update if i find a way to fix it. Nvidia jetson nano models.

The development process is simplified with support for cloud native technologies and developers can go even further with gpu accelerated libraries and sdks. Below are various dnn models for inferencing on jetson with support for tensorrt. Microsoft and nvidia have collaborated to build validate and publish the onnx runtime python package and docker container for the nvidia jetson platform now available on the jetson zoo. I did try using the ssd and yolo v3 models from the zoo.

It is evident from the latency point of view nvidia jetson nano is performing better 25 fps as compared to 9 fps of google coral and 4 fps of intel ncs. I chose the tiny yolo v2 model from the zoo as it was readily compatible with deepstream and was also light enough to run fast on the jetson nano. The model zoo of the three accelerators are listed here. Contribute to dusty nv jetson zoo development by creating an account on github.

Testing with tensorflow 1 8 0 on my jetson tx2 after i set the score threshold to 0 3 the models indeed ran as fast as what nvidia has published. But there were some compatibility issues. Today s release of onnx runtime for jetson extends the performance and portability benefits of onnx runtime to jetson edge ai systems allowing models from many different frameworks to run faster using. You are going to take the fasterrcnn detection model from tensorflow model zoo and create a deepstream pipeline to deploy this model on an nvidia gpu for object detection.

Ssd mobilnet v2 coco could not be tested since the model config file and its checkpoint file do not match. For this post you use the faster rcnn inception v2 coco 2018 01 28 model on the nvidia jetson and nvidia t4. Run an object detection model on nvidia jetson module. It includes a familiar linux environment and brings to each jetson developer the same nvidia cuda x software and tools used by professionals around the world.

The onnx model zoo has a bunch of pre trained object detection models. Intel ncs model zoo and applications. The tensorflow model zoo can help get you started with. Nvidia jetson app store and model zoo.

Is a gnu linux based system software distribution by nvidia for the nvidia tegra processor series such as used in the nvidia jetson board.