Vehicle Axle Detection API

Endpoint Overview

POST /api/v1/ocr/axle-detection

Description

The Vehicle Axle Detection API leverages advanced computer vision and machine learning algorithms to automatically count the number of axles in vehicle images. This endpoint processes uploaded vehicle images and returns an accurate count of axles, enabling automated vehicle classification and compliance verification systems.

The API supports multiple input formats including direct file uploads, base64-encoded images, and image URLs, making it flexible for various integration scenarios. For PDF documents containing vehicle images, the API can extract and analyze images when the use_pdf parameter is enabled.

Key Benefits

Automated Compliance: Streamline toll collection and weight restriction enforcement

High Accuracy: Advanced ML models trained on diverse vehicle datasets

Multiple Input Formats: Support for files, base64, URLs, and PDF extraction

Real-time Processing: Fast response times for operational efficiency

Use Cases

Transportation & Logistics

Government & Regulatory

Insurance & Finance

Automated toll plaza classification for axle-based pricing

Fleet management and vehicle inventory tracking

Loading dock compliance verification

Route planning based on vehicle axle restrictions

Technical Implementation

Authentication

All API requests require authentication using a JWT Bearer token. Authentication follows these steps:

Obtain API Credentials: Register with Surepass to receive your API key.

Generate JWT Token: Use your API key to generate a JWT token.

Include in Requests: Add the token to the Authorization header as Bearer TOKEN.

Different authentication tokens are used for sandbox and production environments:

Sandbox: https://sandbox.surepass.io

Production: https://kyc-api.surepass.io

Request Parameters

Request Headers

Header	Required	Description
Authorization	Yes	Bearer JWT token for API authentication
Content-Type	Yes	multipart/form-data for file uploads

Request Body

Parameter	Type	Required	Description
file	File	Conditional*	Vehicle image file (JPEG, PNG, etc.)
base64	String	Conditional*	Base64-encoded vehicle image
link	String	Conditional*	URL to vehicle image
use_pdf	Boolean	No	Set to true when processing PDF files (default: false)

*One of file, base64, or link is required.

Example Request (Form Data)

POST /api/v1/ocr/axle-detection
Content-Type: multipart/form-data
Authorization: Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...

--boundary
Content-Disposition: form-data; name="file"; filename="vehicle.jpg"
Content-Type: image/jpeg

[Binary image data]
--boundary--

Process Response

Response Parameters

Parameter	Type	Description
data	Object	Container for response data
data.client_id	String	Unique identifier for the processing request
data.axle_count	Integer	Number of axles detected in the vehicle image
status_code	Integer	HTTP status code (200 for success)
success	Boolean	Indicates if the request was processed successfully
message	String	Human-readable response message
message_code	String	Machine-readable status code

Example Successful Response

{
    "data": {
        "client_id": "axle_detection_zgdjiyDgtajejcrwkhOY",
        "axle_count": 5
    },
    "status_code": 200,
    "success": true,
    "message": "success",
    "message_code": "success"
}

Possible Error Responses

Authentication Error

Invalid Image

Invalid File Format

Server Error

{
    "error": null,
    "message": "Your token is invalid. Please ensure that correct token is being used.",
    "status_code": 401,
    "success": false,
    "message_code": "invalid_token"
}

Occurs when the JWT token is missing, invalid, or expired.

Integration Best Practices

Security Recommendations

Store JWT tokens securely and implement proper token refresh mechanisms

Use HTTPS for all API communications to protect sensitive data

Implement proper error handling and avoid exposing sensitive information

Validate and sanitize image inputs before processing

Monitor API usage and implement rate limiting on client side

User Experience Guidelines

Provide clear feedback during image upload and processing

Implement proper loading states with progress indicators

Allow users to preview images before submission

Provide clear error messages for failed detections

Consider implementing client-side image validation for better UX

Code Samples

cURL

Python

Node.js

Related APIs

Vehicle Classification API: Classify vehicle types based on detected characteristics

License Plate Recognition API: Extract and validate license plate information

Vehicle Damage Assessment API: Analyze vehicle images for damage detection

Traffic Violation Detection API: Identify various traffic violations from images

Compliance and Legal Considerations

Ensure compliance with local privacy laws when processing vehicle images

Obtain proper consent for image processing in regulated jurisdictions

Consider data retention policies for processed images and results

Implement audit trails for compliance reporting requirements

Be aware of export control regulations for AI/ML technology usage

{ "data": { "client_id": "axle_detection_zgdjiyDgtajejcrwkhOY", "axle_count": 5 }, "status_code": 200, "success": true, "message": "success", "message_code": "success" }

Provide your bearer token in the

Authorization

header when making requests to protected resources.

Example:

Authorization: Bearer ********************

Axle Detection

Vehicle Axle Detection API#

Description#

Use Cases#

Technical Implementation#

Request Headers#

Request Body#

Example Request (Form Data)#

Response Parameters#

Example Successful Response#

Possible Error Responses#

Integration Best Practices#

Code Samples#

Request

Responses