<jupyter_start><jupyter_text>TensorRT YoloV5s Sample Application --- 1. [Prerequisites](Prerequisites)1. [Set up](Set-up)1. [Import model](Import-model)1. [Write and test app code](Write-and-test-app-code-in-notebook)1. [Package app](Package-app)1. [Deploy app to device](Deploy-app-to-device)  Prerequisites (DO NOT SKIP) 1. **PLEASE READ THE [README](README.md) INCLUDE WITH THIS BEFORE YOU START USING THIS NOTEBOOK**  Set up Import libraries for use with this notebook environment, you do not need these libraries when you write your application code.<jupyter_code>import sys
import os
import time
import json
import boto3
import sagemaker

sys.path.insert( 0, os.path.abspath( "../common/test_utility" ) )
import panorama_test_utility<jupyter_output><empty_output><jupyter_text>Notebook parametersGlobal constants that help the notebook create Panorama resources on your behalf.<jupyter_code># application name
app_name = 'lab3'

## package names and node names
code_package_name = 'lab3'
camera_node_name = 'abstract_rtsp_media_source'

# AWS account ID
account_id = boto3.client("sts").get_caller_identity()["Account"]<jupyter_output><empty_output><jupyter_text>Set up applicationEvery application uses the creator's AWS Account ID as the prefix to uniquely identifies the application resources. Running `panorama-cli import-application` replaces the generic account Id with your account Id.<jupyter_code>!cd ./lab3 && panorama-cli import-application<jupyter_output><empty_output><jupyter_text>Download Depedencies and Artifacts (One Time Download)<jupyter_code>panorama_test_utility.download_artifacts_gpu_sample('lab3', account_id)<jupyter_output><empty_output><jupyter_text>Upload application to Panorama for deploying to devices<jupyter_code>container_asset_name = 'lab3'
# This step takes some time, depending on your network environment.
!cd ./lab3 && pwd && panorama-cli package-application<jupyter_output><empty_output>
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