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Real-Time Frontal Face Detection using SOD RealNets - https://sod.pixlab.io
/*
* Programming introduction with the SOD Embedded RealNets API (Frontal Facial detection).
* Copyright (C) PixLab | Symisc Systems, https://sod.pixlab.io
*/
/*
* Compile this file together with the SOD embedded source code to generate
* the executable. For example:
*
* gcc sod.c realnet_face_detection.c -lm -Ofast -march=native -Wall -std=c99 -o sod_realnet_face_detect
*
* Under Microsoft Visual Studio (>= 2015), just drop `sod.c` and its accompanying
* header files on your source tree and you're done. If you have any trouble
* integrating SOD in your project, please submit a support request at:
* https://sod.pixlab.io/support.html
*/
/*
* This simple program is a quick introduction on how to embed and start
* experimenting with SOD without having to do a lot of tedious
* reading and configuration.
*
* Make sure you have the latest release of SOD from:
* https://pixlab.io/downloads
* The SOD Embedded C/C++ documentation is available at:
* https://sod.pixlab.io/api.html
*/
#include <stdio.h>
#include "sod.h"
int main(int argc, char *argv[])
{
/* Input image (pass a path or use the test image shipped with the samples ZIP archive) */
const char *zFile = argc > 1 ? argv[1] : "./realnet_faces.jpg";
/*
* By default, RealNets are designed to process video streams thanks
* to their very fast processing speed. However, for the sake of simplicity
* we'll stick with images for this programming intro to RealNets.
*/
sod_realnet *pNet; /* Realnet handle */
int i,rc;
/*
* Allocate a new RealNet handle */
rc = sod_realnet_create(&pNet);
if (rc != SOD_OK) return rc;
/*
* Register and load a RealNet model.
* You can train your own RealNet model on your CPU using the training interfaces [sod_realnet_train_start()]
* or download pre-trained models like this one from https://pixlab.io/downloads
*/
rc = sod_realnet_load_model_from_disk(pNet, "./face.realnet.sod", 0);
if (rc != SOD_OK) return rc;
/* Load the target image in grayscale colorspace */
sod_img img = sod_img_load_grayscale(zFile);
if (img.data == 0) {
puts("Cannot load image");
return 0;
}
/* Load a full color copy of the target image so we draw rose boxes
* Note that drawing on grayscale images is also supported.
*/
sod_img color = sod_img_load_color(zFile);
/*
* convert the grayscale image to blob.
*/
unsigned char *zBlob = sod_image_to_blob(img);
/*
* Bounding boxes array
*/
sod_box *aBoxes;
int nbox;
/*
* Perform Real-Time detection on this blob
*/
rc = sod_realnet_detect(pNet, zBlob, img.w, img.h, &aBoxes, &nbox);
if (rc != SOD_OK) return rc;
/* Consume result */
printf("%d potential face(s) were detected..\n", nbox);
for (i = 0; i < nbox; i++) {
/* Ignore low score detection */
if (aBoxes[i].score < 5.0) continue;
/* Report current object */
printf("(%s) x:%d y:%d w:%d h:%d prob:%f\n", aBoxes[i].zName, aBoxes[i].x, aBoxes[i].y, aBoxes[i].w, aBoxes[i].h, aBoxes[i].score);
/* Draw a rose box on the target coordinates */
sod_image_draw_bbox_width(color, aBoxes[i], 3, 255., 0, 225.);
//sod_image_draw_circle(color, aBoxes[i].x + (aBoxes[i].w / 2), aBoxes[i].y + (aBoxes[i].h / 2), aBoxes[i].w, 255., 0, 225.);
}
/* Save the detection result */
sod_img_save_as_png(color, argc > 2 ? argv[2] : "./out.png");
/* cleanup */
sod_free_image(img);
sod_free_image(color);
sod_image_free_blob(zBlob);
sod_realnet_destroy(pNet);
return 0;
}
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@symisc symisc commented Apr 18, 2018

SOD Embedded Homepage: https://sod.pixlab.io
SOD C/C++ API documentation: https://sod.pixlab.io/api.html
Getting Started with SOD Embedded: https://sod.pixlab.io/intro.html

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