The Face Recognition Service is a microservice that provides facial recognition functionalities, including creating a new identity and recognizing faces in images. It exposes two main API endpoints: one for creating a new identity and another for recognizing faces from provided images.
This API allows you to create a new face identity. You need to provide the image data as a base64 encoded string along with the user ID and request ID. The service will register the identity using the specified algorithms for detection and recognition.
POST /face/create-identity
curl --location 'http://localhost:5000/face/create-identity' \
--header 'Content-Type: application/json' \
--data '{
"algorithmDet": "mobilenet",
"algorithmReg": "mobilenet",
"userId": "Mario",
"requestId": "123",
"imageBase64": ""
}'algorithmDet(string): The face detection algorithm to be used (e.g., "mobilenet").algorithmReg(string): The face recognition algorithm to be used (e.g., "mobilenet").userId(string): The user ID associated with the face identity.requestId(string): A unique request ID to track the request.imageBase64(string): The base64 encoded image data of the user's face.
The response will confirm whether the identity creation was successful.
{
"status": "success",
"message": "Identity created successfully"
}This API allows you to recognize a face from an image. It will compare the provided image with the registered identities and return the result of the recognition.
POST /face/recognize
curl --location 'http://localhost:5000/face/recognize' \
--header 'Content-Type: application/json' \
--data '{
"algorithmDet": "mobilenet",
"algorithmReg": "mobilenet",
"userId": "Mario",
"requestId": "123",
"imageBase64": ""
}'algorithmDet(string): The face detection algorithm to be used (e.g., "mobilenet").algorithmReg(string): The face recognition algorithm to be used (e.g., "mobilenet").userId(string): The user ID of the person to recognize.requestId(string): A unique request ID to track the request.imageBase64(string): The base64 encoded image data of the face to be recognized.
The response will include the recognition result, including whether the face was recognized and the matching identity.
{
"code": "0000",
"data": {
"request_id": "123",
"searh_result": {
"Unknown": "0.9998"
},
"user_id": "Mario"
},
"message": "Operation successful."
}code: A status code indicating the operation's success or failure (e.g., "0000" for success).message: A human-readable message providing further details about the result.data:request_id: The unique request ID associated with the recognition request.searh_result: The result of the face recognition (e.g., the similarity score with known identities)."Unknown": The score indicating the match with the "Unknown" face.
user_id: The user ID of the recognized person (if a match is found).
Ensure that the following software is installed:
- Docker
- Docker Compose
-
Clone the repository:
git clone https://github.com/mario-noobs/face-microservice.git cd face-microservice/face-regconition-service -
Build the service:
docker build -t face-recognition-service . -
Run the service:
docker run -p 5000:5000 face-recognition-service
-
The service will be running at
http://localhost:5000.
- Image Base64 Encoding: For the image input in the API requests, you must provide the image as a base64 encoded string. Tools like base64-image.de can help with encoding images into base64 format.
- Algorithms: The service supports various algorithms for face detection and recognition. In this example,
mobilenetis used for both detection and recognition.
-
If the service is not responding as expected, check the logs for errors:
docker logs <container-name>
-
Ensure that the base64 image data is correctly formatted and not empty.
This project is licensed under the MIT License - see the LICENSE file for details.