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.
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.
If the Upload and calibrate API call response contains dataset_id, extrinsic_parameters, and error_stats, the calibration process is completed without errors.
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, and error_stats.
We require pairs of images from Camera-1 and Camera-2 for a given calibration.
Place the images captured from Camera-1 in a folder.
Place the images captured from Camera-2 in a folder.
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.
The names of the folders and the images shown here are for demonstration purposes. Users should avoid using space in the folder and the image names.
The name of the JSON file should be config.json (case sensitive)
calibration_name
string
Name of the calibration
calibration_type
string
Non-editable field.
*Value should be stereo_camera_calibration
calibration_approach
string
Non-editable field.
*Value should be targetless
calibration_group_id
string
This is an optional key. Provide valid calibration_group_id to add the dataset to calibration group.
version
integer
Non-editable field *Value should be kept 1.
type
string
Non-editable field
Describes the kind of sensor, *value should be kept camera
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
order
int
An integer value to differentiate Camera-1 and Camera-2 inputs.
order = 1 for Camera-1
order = 2 for Camera-2
distance_between_two_cameras
double
Distance between Camera-1 and Camera-2 in meters.
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:
If the lens_model is pinhole we require k1, k2, k3, p1, and p2 values (no need of k4)
If the lens_model is fisheye then we require the k1, k2, k3, and k4 values. (p1 and p2 are not needed)
These parameters are not required if distortion_enabled is false.
data
dict
It stores the data related to mapping of the images
mappings
List of lists
It is a list of lists, where each sub-list is a tuple containing names of the images paired together.
Note:
The first element in the tuple should be the image path from the first camera (Camera-1)
The second element in the tuple should be the image path from the second camera (Camera-2).
The client can name their images as they want, but they must have the same name in the mapping list and be present in the suitable folder.
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
This POST api call sends a zip file to the server and runs the calibration algorithm. Returns dataset_id, extrinsic_parameters, and error_stats to the user as the response.
https://tools.calibrate.deepen.ai/api/v2/external/clients/{clientId}/calibration_dataset
clientId
string
ClientId obtained from Deepen AI
file
.zip file
Zip file containing config and images in a suitable format
dataset_id
A unique value to identify the dataset. dataset_id can be used to retrieve the extrinsic parameters.
extrinsic_parameters
roll, pitch, and yaw are given in degrees and px, py, and pz are given in meters.
error_stats
Epiline Point Distance: Average pixel distance of each point to its corresponding projected epiline.
Epipolar Error: Proportional to the distance of a point from its epiline. Does not have a physical meaning. It is the residual error from minimizing the epipolar constraints while calculating the fundamental/essential matrix.
If the data is empty. 'status': "error no files found"
This GET api call returns dataset_id, extrinsic_parameters, and error_stats.
https://tools.calibrate.deepen.ai/api/v2/external/datasets/{datasetId}/extrinsic_parameters
datasetId
string
datasetId obtained from the response of Upload file and calibrate API.
dataset_id
A unique value to identify the dataset. dataset_id can be used to retrieve the extrinsic parameters.
extrinsic_parameters
roll, pitch, and yaw are given in degrees and px, py, and pz are given in meters.
error_stats
Epiline Point Distance: Average pixel distance of each point to its corresponding projected epiline.
Epipolar Error: Proportional to the distance of a point from its epiline. Does not have a physical meaning. It is the residual error from minimizing the epipolar constraints while calculating the fundamental/essential matrix
Missing keys in the config.json (Example: order key is missing)
