Python SDK

Installation

Python Version

Private ID® supports Python 3.6 or greater.

Dependencies

Private ID has dependencies on numpy, scipy and Pillow for image processing. These distributions will be installed automatically. Private ID detects and uses numpy, scipy and Pillow if they are already installed.

• Numpy provides functions for array wise image manipulation.

• Pillow provides functionalities for reading the Image and converting to required formats.

• Scipy provides a faster, more efficient method for comparison of distances and supports shared library functionalities.

Install Private ID PIP package

Within the Python3 environment, use the following command to install the Private ID Python SDK:

pip3 install https://privid-sdk.s3.us-east-2.amazonaws.com/privateid/privateid-1.1.0-py3-none-any.whl

Upgrade Private ID PIP package

To upgrade the PrivateID version, use the following command:

pip3 install --force-reinstall --no-cache https://privid-sdk.s3.us-east-2.amazonaws.com/privateid/privateid-1.1.0-py3-none-any.whl

Install facial recognition Python SDK

This section covers how to use facial recognition SDK for generating and verifying identity.

class privateid.FHE.FaceFactor(server_url, local_storage_path=None, api_key=None)

The FaceFactor class implements the methods for enrolling and predicting. It exposes five methods as part of the interface:

1. enroll: Enrolls the face of the user.

2. predict: Predicts the face of the user.

3. is_valid: Verifies the face of the user.

4. delete: Deletes the enrollment of the user.

5. compare: Compare two faces for verification.

PARAMETERS

• URL : STR

  • The URL of the FaceFactor server.

• LOCAL_STORAGE_PATH : STR (OPTIONAL)

  • Absolute path to the local storage.

• API_KEYSTR - The API key for using the FaceFactor server.

• RETURNS

  • OBJECT
    • Instance of the FaceFactor class.

METHODS

Method	Desc
is_valid(image_path)	Check if the image is valid
enroll(image_path)	Enrolls the image in the face recognition server
predict(image_path)	Predicts the image in the face recognition server
delete(uuid)	Deletes the enrollment from the face recognition server
compare(image_path_1, image_path_2)	Check if the images are of same person or not

delete(uuid: str) → dict

Deletes the enrollment from the face recognition server

• PARAMETERS
  • UUID
    • UUID of the enrolled image
• RETURNS
  • DICT - Status and message of the operation.
    • SUCCESSFUL OPERATION: { “status”: 0, “message”: “OK” }
    • UNSUCCESSFUL OPERATION: { “status”: -1, “message”: “error message” }

enroll(image_path: str) → dict

Enrolls the image in the face recognition server

• PARAMETERS
  • IMAGE_PATH
    • Directory path to the image file
• RETURNS
  • DICT - Status and message of the operation.
    • SUCCESSFUL OPERATION: { “status”: 0, “message”: “success”, “uuid”: UUID }
    • UNSUCCESSFUL OPERATION: { “status”: -1, “message”: “error message” }

is_valid(image_path: str_) → dict Check if the image is valid for using in the face recognition

• PARAMETERS
  • IMAGE_PATH
    • Directory path to the image file
• RETURNS
  • DICT - Status and message of the operation
    • SUCCESSFUL OPERATION: { “status”: 0, “message”: “Valid image” }
    • UNSUCCESSFUL OPERATION: { “status”: -1, “message”: “Invalid image” }

predict(image_path: str_) → dict Predicts the image in the face recognition server

• PARAMETERS
  • IMAGE_PATH
    • Directory path to the image file
  • RETURNS
    • DICT - Status and message of the operation.
      • SUCCESSFUL OPERATION: { ‘status’: 0, ‘message’: ‘success’, ‘uuid’: UUID }
      • UNSUCCESSFUL OPERATION: { “status”: -1, “message”: “error message” }

compare(self, image_path_1: str_, image_path_2: str_) → dict Compare two faces for verification

• PARAMETERS
  • IMAGE_PATH_1
    • Directory path to the image file 1
  • IMAGE_PATH_2
    • Directory path to the image file 2
  • RETURNS
    • DICT - Status and message of the operation.

      • SUCCESSFUL OPERATION (same person): { ’status’: 0,’message’: ’Person in both the image is same.’ }

      • SUCCESSFUL OPERATION (different person): { ’status’: 1, ’message’: ’Person in the images is not same.’ }

      • UNSUCCESSFUL OPERATION: { ’status’: -1, ’message’: ’Invalid image or some error.’ }

Virtual environments (optional)

Use a native Python environment from your OS or a virtual environment to manage the dependencies for your project, both in development and in production. This section addresses use of a virtual environment.

What problem does a virtual environment solve? The more Python projects you have, the more likely it is that you need to work with different versions of Python libraries, or even Python itself. Newer versions of libraries for one project can break compatibility in another project.

Virtual environments are independent groups of Python libraries, one for each project. Packages installed for one project will not affect other projects or the operating system’s packages.

Python comes bundled with the venv module to create virtual environments.

Create an environment

Create a project folder and a venv folder within:

mkdir myproject
cd myproject
python3 -m venv venv

On Windows:

py -3 -m venv venv

Activate the environment

Before you work on your project, activate the corresponding environment:

. venv/bin/activate

On Windows:

venv\Scripts\activate

Your shell prompt will change to show the name of the activated environment.

Return Codes and Message Desciprtions

Return Code	Return Message / Error Description
0	Valid Image
1	Face is an image of an image (spoof). Please only provide live facial image(s). (Under implementation)
2	Face is an image of a video (spoof). Please only provide live facial image(s). (Under implementation)
3	Face in image is too close to the camera. Please move away from the camera.
4	Face in image is too far away.
5	Face in image is too far to the right.
6	Face in image is too far to the left.
7	Face in image is too high.
8	Face in image is too low.
9	Face in image is too blurry.
10	Please remove eyeglasses during registration.
11	Please remove face mask during registration.
12	Head in image turned too far toward the left/right. Please face the camera.
13	Head in image turned too far up/down. Please face the camera.
14	Reserved for future use.
15	Reserved for future use.
16	No face found in image.
17	API Error
18	Local Storage Error
19	Memory Error