mrtj

{
    "name": "model_node",
    "interface": "<AWS_ACCOUNT_ID>::yolox_s.interface",
    "overridable": false,
    "launch": "onAppStart"
}

mrtj

AWS_ACCOUNT_ID=$(aws sts get-caller-identity --output text --query 'Account')
panorama-cli add-raw-model \
    --model-asset-name yolox_s_asset \
    --model-local-path [model_archive_path]/yolox_s_torchscript.tar.gz \
    --descriptor-path packages/${AWS_ACCOUNT_ID}-yolox_s-1.0/descriptor.json \
    --packages-path packages/${AWS_ACCOUNT_ID}-yolox_s-1.0

mrtj

"edges": [
    {
        "producer": "camera_node.video_out",
        "consumer": "code_node.video_in"
    },
    {
        "producer": "code_node.video_out",
        "consumer": "display_node.video_in"
    },
    {

mrtj

{
    "name": "detection_threshold",
    "interface": "float32",
    "value": 20.0,
    "overridable": true,
    "decorator": {
        "title": "Threshold",
        "description": "The minimum confidence percentage for a positive classification."
    }
}

mrtj

{
    "name": "code_node",
    "interface": "123456789012::application_logic.interface"
},
{
    "name": "model_node",
    "interface": "123456789012::yolox_s.interface"
}

mrtj

panorama-cli add-panorama-package --type camera --name camera_input
panorama-cli add-panorama-package --type data_sink --name display_output
panorama-cli create-package --type Container --name application_logic
panorama-cli create-package --type Model --name yolox_s

mrtj

#!/usr/bin/env bash
cat train.csv | sed 's/ /_/g' | sed 's/,/ /g' | awk '{print $1}' | grep "$1" | sort | uniq

mrtj

import boto3
bucket, prefix = 'my_bucket', 'datasets/dogs_vs_cats'
paginator = boto3.client('s3').get_paginator('list_objects')
with open('manifest.jsonl', 'w') as f:
    for page in paginator.paginate(Bucket=bucket, Prefix=prefix):
        for obj in page['Contents']:
            lbl = 0 if 'dog.' in obj['Key'] else 1
            f.write('{{"source-ref":"s3://{}/{}", "class":"{}"}}\n'\
                .format(bucket, obj['Key'], lbl))

mrtj

aws stepfunctions start-execution \
  - state-machine-arn {CrossValidatorStateMachineArn} \
  - input file://my_input.json

mrtj

import glob
prefix = 's3://my_bucket/dogs_vs_cats/'
with open('manifest.jsonl', 'w') as f:
    for img in glob.glob('*.jpg'):
        lbl = 0 if img.startswith('dog') else 1
        f.write('{{"source-ref":"{}{}", "class":"{}"}}\n'\
                .format(prefix, img, lbl))