Targetless Camera-Vehicle Calibration API

Introduction

The API requires the client to upload the images and configuration for camera setup in a zip file (.zip extension) in the format defined below. The contents of the zip file are called a dataset.

1. The client makes an Upload and calibrate API call, which uploads their files and runs the calibration algorithm on the images for the given configuration.

2. The calibration process is completed without errors if the Upload and calibrate API call response contains dataset_id, calibration_algorithm_version and extrinsic_parameters.

3. The client can call the Get Extrinsic Parameters API using the dataset_id obtained from the Upload and calibrate API. This API responds with dataset_id, extrinsic_parameters, calibration_algorithm_version, extrinsic_parameters, and error_stats.

Folder Structure

We require images from the camera and other configurations to calculate extrinsic parameters.

1. Place the images captured from the camera in a folder.

2. config.json contains configuration details of the calibration (intrinsic parameters, calibration name, etc.)

Note: Folder structure is optional. Users can place all files in the main directory and zip it.

All files in main directory

Note

1. The names of the folders and the images shown here are for demonstration purposes. Users should avoid using space in the folder and image filenames.

2. The name of the JSON file should be config.json (case sensitive)

config.json for targetless camera vehicle

{
    "calibration_name": "sample targetless vehicle calibration",
    "calibration_type": "camera_vehicle_calibration",
    "calibration_group_id": "XXXXXXXXXXXXXXXXX",
    "is_target_based": false,
    "intrinsics":
    {
        "camera_name": "Front",
        "camera_fov_direction": "front",
        "fx": 924.8888151455135,
        "fy": 927.1330690835912,
        "cx": 950.9444853761762,
        "cy": 574.8548162684357,
        "lens_model": "pinhole",
        "k1": -0.37373087093017543,
        "k2": 0.2006217414922034,
        "k3": -0.06745835388849057,
        "k4": 0,
        "k5": 0,
        "k6": 0,
        "p1": -0.0014548541893372843,
        "p2": -0.00044277672802422454,
        "distortion_enabled": true
    },
    "target_configuration":
    {
        "file_data":
        [
            {
                "file_name": "out1.png"
            },
            {
                "file_name": "out5.png"
            },
            {
                "file_name": "out10.png"
            },
            {
                "file_name": "out15.png"
            },
            {
            	"file_name": "out20.png"
            }
        ]
    }
}

Sample config.json

1KB

config.json

config.json key description

Key	Type	Description
calibration_name	String	Name of the calibration
calibration_type	String	Non-editable field. Value should be camera_vehicle_calibration
calibration_group_id	String	This is an optional key. Provide valid calibration_group_id to add the dataset to calibration group.
intrinsics	Object	Intrinsic parameters of the camera used for data collection.
camera_name	string	It is the name given by the client to the camera. The client can modify it as willed.
lens_model	string	Describes the type of lens used by the camera. Accepted values pinhole fisheye kannalabrandt
fx	double	Focal length of the cameras in the X-axis. Value in pixels.
fy	double	Focal length of the camera in the Y-axis. Value in pixels.
cx	double	Optical centre of the camera in the X-axis. Value in pixels.
cy	double	Optical centre of the camera in the Y-axis. Value in pixels.
distortion_enabled	boolean	Makes use of distortion coefficients (k1, k2, k3, k4, p1, p2) for the calibration algorithm when set true. Distortion coefficients (k1, k2, k3, k4, p1, p2) are not required if it is false.
k1, k2, k3, k4, k5, k6, k7, k8,p1, p2	double	These are the values for distortion coefficients of the camera lens.Note: If the lens_model is pinhole we require k1, k2, k3, p1, and p2 values (no need of k4-k8) If the lens_model is fisheye then we require the k1, k2, k3, and k4 values. (k5-k8,p1 and p2 are not needed) if the lens_model is kannalbrandt we require k1-k8. ( p1 and p2 values are not needed) These parameters are not required if distortion_enabled is false.
file_data	List of Objects	It is a list of Objects, where each Object is a image and it's corresponding configuration. file_name: The name of the file (including the path in zip file).
target_configuration	Object	wrapper around file_data . for consistency with targetbased.

Quickstart

Before invoking the APIs, the client must obtain the clientId and auth token from Deepen AI. If you are a calibration admin, you can create different Access Tokens using the UI and use those instead. clientId is part of the path parameters in most API calls, and the auth token should be prefixed with “Bearer“ and passed to the ‘Authorization’ header in all API requests. How to get Access Tokens can be found on the following link: Access token for APIs

Upload file and calibrate

This POST api call sends a zip file to the server and runs the calibration algorithm. Returns dataset_id, extrinsic_camera_coordinate_system, calibration_algorithm_version, extrinsic_parameters, and error_stats to the user as the response.

https://tools.calibrate.deepen.ai/api/v2/external/clients/{clientId}/calibration_dataset

Request

Path parameters

Parameter name	Parameter type	Description
clientId	string	ClientId obtained from Deepen AI

Body

Key	Value	Description
file	.zip file	Zip file containing config and images in a suitable format

Response

{
    "dataset_id": "XXXXXXXXXXXXXX",
    "calibration_algorithm_version": "XXXXXXXXXXXXXXXXXXX",
    "extrinsic_parameters": {
        "roll": -3.532592830669066,
        "pitch": 2.631748940982094,
        "yaw": 0.9289737684506295
    }
}

Key	Description
dataset_id	A unique value to identify the dataset. dataset_id can be used to retrieve the extrinsic parameters.
calibration_algorithm_version	The version of the algorithm used to calculate extrinsic parameters. This value can be used to map extrinsic parameters to a specific algorithm version.
extrinsic_parameters	roll, pitch, and yaw are given in degrees.

Get Extrinsic Parameters

This GET api call returns dataset_id, extrinsic_camera_coordinate_system, calibration_algorithm_version, extrinsic_parameters, and error_stats to the user as the response.

https://tools.calibrate.deepen.ai/api/v2/external/datasets/{dataset_id}/extrinsic_parameters

Request

Path parameters

Parameter name	Parameter type	Description
dataset_id	string	dataset_id obtained from the response of Upload file and calibrate API.

Response

{
    "dataset_id": "XXXXXXXXXXXXXXXXX",
    "extrinsic_parameters": {
        "roll": -96.93828475587402,
        "pitch": -2.589261966902198,
        "yaw": -91.64337716058188,
    },
    "calibration_algorithm_version": "XXXXXXXXXXXXXXXXXX"
}

Key	Description
dataset_id	A unique value to identify the dataset. dataset_id can be used to retrieve the extrinsic parameters.
calibration_algorithm_version	The version of the algorithm used to calculate extrinsic parameters. This value can be used to map extrinsic parameters to a specific algorithm version.
extrinsic_parameters	roll, pitch, and yaw are given in degrees.