|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
#include "net.h" |
|
|
|
#if defined(USE_NCNN_SIMPLEOCV) |
|
#include "simpleocv.h" |
|
#else |
|
#include <opencv2/core/core.hpp> |
|
#include <opencv2/highgui/highgui.hpp> |
|
#include <opencv2/imgproc/imgproc.hpp> |
|
#endif |
|
#include <stdio.h> |
|
#include <vector> |
|
|
|
struct Object |
|
{ |
|
cv::Rect_<float> rect; |
|
int label; |
|
float prob; |
|
}; |
|
|
|
static int detect_mobilenet(const cv::Mat& bgr, std::vector<Object>& objects) |
|
{ |
|
ncnn::Net mobilenet; |
|
|
|
mobilenet.opt.use_vulkan_compute = true; |
|
|
|
|
|
|
|
|
|
if (mobilenet.load_param("mobilenet_ssd_voc_ncnn.param")) |
|
exit(-1); |
|
if (mobilenet.load_model("mobilenet_ssd_voc_ncnn.bin")) |
|
exit(-1); |
|
|
|
const int target_size = 300; |
|
|
|
int img_w = bgr.cols; |
|
int img_h = bgr.rows; |
|
|
|
ncnn::Mat in = ncnn::Mat::from_pixels_resize(bgr.data, ncnn::Mat::PIXEL_BGR, bgr.cols, bgr.rows, target_size, target_size); |
|
|
|
const float mean_vals[3] = {127.5f, 127.5f, 127.5f}; |
|
const float norm_vals[3] = {1.0 / 127.5, 1.0 / 127.5, 1.0 / 127.5}; |
|
in.substract_mean_normalize(mean_vals, norm_vals); |
|
|
|
ncnn::Extractor ex = mobilenet.create_extractor(); |
|
|
|
ex.input("data", in); |
|
|
|
ncnn::Mat out; |
|
ex.extract("detection_out", out); |
|
|
|
|
|
objects.clear(); |
|
for (int i = 0; i < out.h; i++) |
|
{ |
|
const float* values = out.row(i); |
|
|
|
Object object; |
|
object.label = values[0]; |
|
object.prob = values[1]; |
|
object.rect.x = values[2] * img_w; |
|
object.rect.y = values[3] * img_h; |
|
object.rect.width = values[4] * img_w - object.rect.x; |
|
object.rect.height = values[5] * img_h - object.rect.y; |
|
|
|
objects.push_back(object); |
|
} |
|
|
|
return 0; |
|
} |
|
|
|
static void draw_objects(const cv::Mat& bgr, const std::vector<Object>& objects) |
|
{ |
|
static const char* class_names[] = {"background", |
|
"aeroplane", "bicycle", "bird", "boat", |
|
"bottle", "bus", "car", "cat", "chair", |
|
"cow", "diningtable", "dog", "horse", |
|
"motorbike", "person", "pottedplant", |
|
"sheep", "sofa", "train", "tvmonitor" |
|
}; |
|
|
|
cv::Mat image = bgr.clone(); |
|
|
|
for (size_t i = 0; i < objects.size(); i++) |
|
{ |
|
const Object& obj = objects[i]; |
|
|
|
fprintf(stderr, "%d = %.5f at %.2f %.2f %.2f x %.2f\n", obj.label, obj.prob, |
|
obj.rect.x, obj.rect.y, obj.rect.width, obj.rect.height); |
|
|
|
cv::rectangle(image, obj.rect, cv::Scalar(255, 0, 0)); |
|
|
|
char text[256]; |
|
sprintf(text, "%s %.1f%%", class_names[obj.label], obj.prob * 100); |
|
|
|
int baseLine = 0; |
|
cv::Size label_size = cv::getTextSize(text, cv::FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine); |
|
|
|
int x = obj.rect.x; |
|
int y = obj.rect.y - label_size.height - baseLine; |
|
if (y < 0) |
|
y = 0; |
|
if (x + label_size.width > image.cols) |
|
x = image.cols - label_size.width; |
|
|
|
cv::rectangle(image, cv::Rect(cv::Point(x, y), cv::Size(label_size.width, label_size.height + baseLine)), |
|
cv::Scalar(255, 255, 255), -1); |
|
|
|
cv::putText(image, text, cv::Point(x, y + label_size.height), |
|
cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0)); |
|
} |
|
|
|
cv::imshow("image", image); |
|
cv::waitKey(0); |
|
} |
|
|
|
int main(int argc, char** argv) |
|
{ |
|
if (argc != 2) |
|
{ |
|
fprintf(stderr, "Usage: %s [imagepath]\n", argv[0]); |
|
return -1; |
|
} |
|
|
|
const char* imagepath = argv[1]; |
|
|
|
cv::Mat m = cv::imread(imagepath, 1); |
|
if (m.empty()) |
|
{ |
|
fprintf(stderr, "cv::imread %s failed\n", imagepath); |
|
return -1; |
|
} |
|
|
|
std::vector<Object> objects; |
|
detect_mobilenet(m, objects); |
|
|
|
draw_objects(m, objects); |
|
|
|
return 0; |
|
} |
|
|