Object Detection

3min

The below parameters are for various Object Detection attacks. To know more about the different attack input parameters see Object Detection﻿﻿
The values presented below are examples taken from the YOLO model used in the reference implementation. It is important to customize these values to achieve the best performance for your particular model.
Json Payload
Evasion
{
"normalize_data": "yes",
"model_framework": "onnx",
"defense_bestonly": "no",
"model_api_details": "na",
"use_model_api": "no",
            
}
{
"normalize_data": "yes",
"model_framework": "onnx",
"defense_bestonly": "no",
"model_api_details": "na",
"use_model_api": "no",
            
}
﻿
POST
Request
Path Params
model_id
optional
String
Header Parameters
x-api-key
required
String
Enter your API key
Org_id
required
String
Enter your organization id
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Note: In the response, job_id and dashboard link will be available. Save these which would be used to track progress and download artifacts. 
For using Nodejs sample code, install npm package request
Given sample code for python is tested for Python version 3.7
Given Sample code for nodejs and javascript is tested for Node V20LTS
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Updated 05 Aug 2024

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