c-face-recognition-h.md

C_API: face_recognition.h

The face_recognition.h header provides function definitions that can be used for accessing the OpenDR face recognition tool.

Struct face_recognition_model_t

struct face_recognition_model {
...
};
typedef struct face_recognition_model face_recognition_model_t;

The face_recognition_model_t structure keeps all the neccesary information that are required by the OpenDR face recognition tool (e.g., model weights, normalization information, database for person recognition, ONNX session information, etc.).

Function load_face_recognition_model()

void load_face_recognition_model(const char *model_path, face_recognition_model_t *model);

Loads a face recognition model saved in the local filesystem (model path) in OpenDR format. This function also initializes a CPU-based ONNX session for performing inference using this model. The pre-trained models should follow the OpenDR conventions. The Python API can be used to train and export an optimized OpenDR model that can be used for inference using the C API.

Function free_face_recognition_model()

void free_face_recognition_model(face_recognition_model_t *model);

Releases the memory allocated for a face recognition model (model).

Function infer_face_recognition()

opendr_category_target_t infer_face_recognition(face_recognition_model_t *model, opendr_image_t *image);

This function perform inference using a face recognition model (model) and an input image (image). The function returns an OpenDR category structure with the inference results.

Function decode_category_face_recognition()

void decode_category_face_recognition(face_recognition_model_t *model, opendr_category_target_t category, char *person_name);

Returns the name of a recognized person by decoding the category id into a string (this function uses the information from the built person database).

Function build_database_face_recognition()

void build_database_face_recognition(const char *database_folder, const char *output_path, face_recognition_model_t *model);

Build a face recognition database (containing images for persons to be recognized). This function expects the database_folder to have the same format as the main Python toolkit. The function calculates the features of the person that are contained in the database and it stores it into a binary file that can be then loaded to perform inference (output_path). A loaded face recongition model should be provided (model), since this model will be used for the feature extraction process.

Function load_database_face_recognition()

void load_database_face_recognition(const char *database_path, face_recognition_model_t *model);

Loads an already built database (*database_path) into a face recognition model (model). After this step, the model can be used for performing inference.