Deepen AI

Radar Camera 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 and lidar files 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, extrinsic_parameters, and error_stats.

  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, calibration_algorithm_version, extrinsic_parameters, and error_stats.

Folder Structure

We require the images from the camera for a given calibration.

  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.

Note

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

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

config.json

{
    "calibration_name": "Radar camera calibration",
    "calibration_type": "radar_camera_calibration",
    "calibration_group_id": "xxxxxxxxxxxxxxxxxx",
    "multi_target": true,
    "intrinsics":
    {
        "camera_name": "camera name",
        "fx": 2204.465766956982,
        "fy": 2200.718949580785,
        "cx": 1987.2093520754504,
        "cy": 1489.9660572902758,
        "k1": -0.23936177115777293,
        "k2": 0.08598068870627995,
        "p1": -0.00022312630506811154,
        "p2": -0.00014031224535402575,
        "k3": -0.017426786421056686,
        "camera_model": "pinhole",
        "distortion_enabled": true
    },
    "targets":
    {
        "0":
        {
            "rows": 14,
            "columns": 14,
            "type": "charucoboard",
            "square_size": 0.08708571428,
            "marker_size": 0.06966857142,
            "dictionary": "5X5",
            "padding_right": 0,
            "padding_left": 0,
            "padding_top": 0,
            "padding_bottom": 0,
            "thickness": 0.017,
            "reflector_edge_length": 0.15
        },
        "1":
        {
            "rows": 13,
            "columns": 13,
            "type": "charucoboard",
            "square_size": 0.09378461538,
            "marker_size": 0.0750276923,
            "dictionary": "6X6",
            "padding_right": 0,
            "padding_left": 0,
            "padding_top": 0,
            "padding_bottom": 0,
            "thickness": 0.017,
            "reflector_edge_length": 0.097
        }
    },
    "radar_targets":
    {
        "file_data":
        [
            {
                "file_name": "IMG_20231026_171948_00_035.jpg",
                "position":
                {
                    "0":
                    {
                        "x": -1.117985,
                        "y": 1.391907,
                        "z": -0.111471
                    },
                    "1":
                    {
                        "x": 0.077714,
                        "y": 2.48555,
                        "z": -0.018687
                    }
                }
            },
            {
                "file_name": "IMG_20231026_173234_00_036.jpg",
                "position":
                {
                    "0":
                    {
                        "x": -1.117985,
                        "y": 1.390701,
                        "z": -0.125626
                    },
                    "1":
                    {
                        "x": 0.850759,
                        "y": 1.913570,
                        "z": 0.005958
                    }
                }
            },
            {
                "file_name": "IMG_20231026_174525_00_037.jpg",
                "position":
                {
                    "0":
                    {
                        "x": -1.183428,
                        "y": 2.430081,
                        "z": 0.105416
                    },
                    "1":
                    {
                        "x": 0.514892,
                        "y": 1.679770,
                        "z": -0.000271
                    }
                }
            },
            {
                "file_name": "IMG_20231026_175017_00_038.jpg",
                "position":
                {
                    "0":
                    {
                        "x": 0.744415,
                        "y": 1.673840,
                        "z": 0.042591
                    },
                    "1":
                    {
                        "x": -1.413842,
                        "y": 2.254565,
                        "z": -0.027773
                    }
                }
            },
            {
                "file_name": "IMG_20231026_175521_00_039.jpg",
                "position":
                {
                    "0":
                    {
                        "x": 0.644887,
                        "y": 1.761710,
                        "z": -0.001819
                    },
                    "1":
                    {
                        "x": -1.413842,
                        "y": 2.253737,
                        "z": -0.067103
                    }
                }
            }
        ]
    }
}

Sample config.json

config.json key description

KeyTypeDescription

calibration_name

string

Name of the calibration

calibration_type

string

Non-editable field. Value should be radar_camera_calibration

calibration_group_id

string

This is an optional key. Provide valid calibration_group_id to add the dataset to calibration group.

multi_target

boolean

true: if multiple targets are used false: if single target is used

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

  1. pinhole

  2. fisheye

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, p1, p2

double

These are the values for distortion coefficients of the camera lens.Note:

  1. If the lens_model is pinhole we require k1, k2, k3, p1, and p2 values (no need of k4)

  2. If the lens_model is fisheye then we require the k1, k2, k3, and k4 values. (p1 and p2 are not needed)

  3. These parameters are not required if distortion_enabled is false.

targets

Object

It is a dictionary of dictionary with each dictionary having target properties

type

string

Describes the type of target used. Accepted values

  1. checkerboard

  2. charucoboard

x (or) horizontal_corners

integer

number of horizontaol corners in the checkerboard (this property is needed if the type = checkerboard)

y (or) vertical_corners

integer

number of vertical corners in the checkerboar (this property is needed if the type = checkerboard)

rows

integer

number of horizontaol squares in the charucoboard (this property is needed if the type is charucoboard)

columns

integer

number of vertical squares in the charucoboard (this property is needed if the type is charcuboard)

square_size

double

Size of each square in meters

marker_size

double

The size of marker in a charucoboard in meters ( Normally it is 0.8 times of square size ) (this property is needed if the type is charucoboard)

dictionary

string

It is the string that defines the charuco dictionary of the target. We support

  1. 4X4

  2. 5X5

  3. 6X6

  4. 7X7

  5. original

  6. charuco_apriltag_36h11

  7. charuco_apriltag_25h9

This property is needed if the type is charucoboard

padding_right

double

padding to the right of the board

padding_left

double

padding to the left of the board

padding_top

double

padding to the top of the board

padding_bottom

double

padding to the bottom of the board

radar_targets

Object

It stores the data related to position of radar target

file_data

List of Objects

It stores the file_name and position

file_name

String

Name of the image file (a file with this name should be available in the zip file)

position

Object

Contains the x, y and z coordinates of the radar-target.

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, 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 nameParameter typeDescription

clientId

string

ClientId obtained from Deepen AI

Body

KeyValueDescription

file

.zip file

Zip file containing config and images in a suitable format

Response

{
    "dataset_id": "XXXXXXXXXXXXXXXXX",
    "calibration_algorithm_version": "XXXXXXXXXXXXXXXXX",
    "extrinsic_parameters": {
        "roll": -90.47755237974575,
        "pitch": -0.38434110269976385,
        "yaw": -87.95967045393508,
        "px": 0.06958801619530329,
        "py": -0.28251980028661544,
        "pz": -0.010306058948604074
    },
    "error_stats": {
        "translation_error": {
            "IMG_20231026_171948_00_035.jpg": 0.3020655174664843,
            "IMG_20231026_173234_00_036.jpg": 0.30081030974787387,
            "IMG_20231026_174525_00_037.jpg": 0.07071623324393249,
            "IMG_20231026_175017_00_038.jpg": 0.23386259022431746,
            "IMG_20231026_175521_00_039.jpg": 0.24004605472611307
        },
        "mean_translation_error": 0.24997455895028214,
        "reprojection_error": {
            "IMG_20231026_171948_00_035.jpg": 278.64663357313,
            "IMG_20231026_173234_00_036.jpg": 306.10811229939486,
            "IMG_20231026_174525_00_037.jpg": 130.23295364437632,
            "IMG_20231026_175017_00_038.jpg": 304.5295288314502,
            "IMG_20231026_175521_00_039.jpg": 352.52075250097744
        },
        "mean_reprojection_error": 274.40759616986577
    }
}
KeyDescription

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 and px, py, and pz are given in meters.

error_stats

translation_error: The translational error rate gives the mean distance error between points in 3D (it is for individual files)

mean_translation_error: Mean of the translation_error of all the files.

reprojection_error: The reprojection error rate gives the mean distance error between points in 2D (it is for individual files) mean_reprojection_error: Mean of the reprojection_error of all the files

Get Extrinsic Parameters

This GET api call returns dataset_id, 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 nameParameter typeDescription

dataset_id

string

dataset_id obtained from the response of Upload file and calibrate API.

Response

{
    "dataset_id": "XXXXXXXXXXXXXXXXX",
    "calibration_algorithm_version": "XXXXXXXXXXXXXXXXX",
    "extrinsic_parameters": {
        "roll": -90.47755237974575,
        "pitch": -0.38434110269976385,
        "yaw": -87.95967045393508,
        "px": 0.06958801619530329,
        "py": -0.28251980028661544,
        "pz": -0.010306058948604074
    },
    "error_stats": {
        "translation_error": {
            "IMG_20231026_171948_00_035.jpg": 0.3020655174664843,
            "IMG_20231026_173234_00_036.jpg": 0.30081030974787387,
            "IMG_20231026_174525_00_037.jpg": 0.07071623324393249,
            "IMG_20231026_175017_00_038.jpg": 0.23386259022431746,
            "IMG_20231026_175521_00_039.jpg": 0.24004605472611307
        },
        "mean_translation_error": 0.24997455895028214,
        "reprojection_error": {
            "IMG_20231026_171948_00_035.jpg": 278.64663357313,
            "IMG_20231026_173234_00_036.jpg": 306.10811229939486,
            "IMG_20231026_174525_00_037.jpg": 130.23295364437632,
            "IMG_20231026_175017_00_038.jpg": 304.5295288314502,
            "IMG_20231026_175521_00_039.jpg": 352.52075250097744
        },
        "mean_reprojection_error": 274.40759616986577
    }
}
KeyDescription

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 and px, py, and pz are given in meters.

error_stats

translation_error: The translational error rate gives the mean distance error between points in 3D (it is for individual files).

mean_translation_error: Mean of the translation_error of all the files.

reprojection_error: The reprojection error rate gives the mean distance error between points in 2D (it is for individual files) mean_reprojection_error: Mean of the reprojection_error of all the files

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