roc_example_verify_embedded.c

Source code for examples/roc_example_verify_embedded.c.

/*
 * This example application takes as input two PGM image paths (presumed to have
 * one face in each image) and outputs the similarity between the face in each
 * image using the Embedded API. Similarity values toward one indicate the two
 * faces appear to be the same person. Similarity values toward zero indicate
 * the two faces appear to be different people. See the API documentation for
 * details regarding how similarity scores are normalized.
 *
 * To compile this example on OS X / Linux (bash):
 *
 *     $ gcc -o roc-example-verify-embedded roc_example_verify_embedded.c -I ../include/ -L ../lib/ -Wl,-rpath,'$ORIGIN/../lib:../lib' -lroc_embedded
 *
 * To compile this example on Windows (Visual Studio Command Prompt):
 *
 *     $ cl roc_example_verify_embedded.c /I ../include/ ../lib/roc.lib /Feroc-example-verify-embedded.exe
 *
 * To run this application using two of the example images:
 *
 *     $ ./roc-example-verify-embedded ../data/josh_1.ppm ../data/josh_2.ppm
 */

#include <stdio.h>
#include <stdlib.h>

#include "roc-embedded.h"

int main(int argc, char *argv[])
{
    roc_image color[2];
    roc_image gray[2];
    uint8_t templates[2 * ROC_FAST_FV_SIZE];
    roc_similarity similarity;
    size_t adaptive_minimum_size, n;
    roc_detection detection;
    roc_landmark *landmarks;
    roc_landmark right_eye, left_eye, chin;
    float quality;
    int i;

    if (argc != 3)
        roc_ensure("Expected two image path arguments:\n"
                   "    $ roc-example-verify-embedded path/to/image_a.ppm path/to/image_b.ppm");

    // Initialize SDK
    roc_ensure(roc_embedded_error_to_string(roc_embedded_initialize(NULL)));

    // Open both images
    for (i=0; i<2; i++) {
        roc_ensure(roc_read_ppm(argv[i+1], &color[i]));
        roc_ensure(roc_bgr2gray(color[i], &gray[i]));
    }

    // Find and represent one face in each image
    for (i=0; i<2; i++) {
        roc_ensure(roc_adaptive_minimum_size(color[i].width, color[i].height, ROC_SUGGESTED_RELATIVE_MIN_SIZE, ROC_SUGGESTED_ABSOLUTE_MIN_SIZE, &adaptive_minimum_size));
        roc_ensure(roc_embedded_error_to_string(roc_embedded_detect_faces(gray[i], adaptive_minimum_size, 1, ROC_SUGGESTED_FALSE_DETECTION_RATE, &n, &detection)));
        if (n != 1)
            roc_ensure("Failed to detect a face!");

        landmarks = (roc_landmark*) malloc(roc_num_landmarks_for_pose(detection.pose) * sizeof(roc_landmark));
        roc_ensure(roc_embedded_error_to_string(roc_embedded_landmark_face(gray[i], &detection, &landmarks[0], &right_eye, &left_eye, &chin, NULL, NULL)));
        free(landmarks);

        float age;
        roc_embedded_gender gender;
        float analytics_spoof;
        roc_ensure(roc_embedded_error_to_string(roc_embedded_represent_face(color[i], detection, right_eye, left_eye, chin, &templates[i*ROC_FAST_FV_SIZE], &quality, &age, NULL, &gender, NULL, NULL, NULL, NULL, NULL, &analytics_spoof, NULL)));

        float spoof;
        roc_ensure(roc_embedded_error_to_string(roc_embedded_liveness(gray[i], right_eye, left_eye, chin, &spoof)));
        spoof = (spoof + analytics_spoof) / 2.f; // We recommend averaging these two responses for the highest accuracy

        printf("Face X: %d   Y: %d   Width: %d   Height: %d   Quality: %.3f   Age: %d   Gender: %c   Spoof: %c\n", (int) detection.x, (int) detection.y, (int) detection.width, (int) detection.height, quality, (int) age, (gender.female > gender.male ? 'F' : 'M'), (spoof > ROC_CONVENIENT_SPOOF_THRESHOLD ? 'Y' : 'N'));
    }

    // Compare faces
    similarity = roc_embedded_compare_templates(&templates[0*ROC_FAST_FV_SIZE], ROC_FAST_FV_SIZE, &templates[1*ROC_FAST_FV_SIZE], ROC_FAST_FV_SIZE);
    printf("Similarity: %.3f\n", similarity);

    // Cleanup
    for (i=0; i<2; i++) {
        roc_ensure(roc_free_image(color[i]));
        roc_ensure(roc_free_image(gray[i]));
    }
    roc_ensure(roc_embedded_error_to_string(roc_embedded_finalize()));
    return EXIT_SUCCESS;
}