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Performance fixes for yolox-tensorrt demo #1342

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Performance fixes for yolox-tensorrt demo #1342

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48 changes: 20 additions & 28 deletions demo/TensorRT/cpp/yolox.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -50,8 +50,8 @@ cv::Mat static_resize(cv::Mat& img) {
struct Object
{
cv::Rect_<float> rect;
int label;
float prob;
int label{};
float prob{};
};

struct GridAndStride
Expand All @@ -61,20 +61,22 @@ struct GridAndStride
int stride;
};

static void generate_grids_and_stride(std::vector<int>& strides, std::vector<GridAndStride>& grid_strides)
static std::vector<GridAndStride> generate_grids_and_stride(std::vector<int>& strides_)
{
for (auto stride : strides)
std::vector<GridAndStride> grid_and_strides{};
for (auto stride : strides_)
{
int num_grid_y = INPUT_H / stride;
int num_grid_x = INPUT_W / stride;
for (int g1 = 0; g1 < num_grid_y; g1++)
{
for (int g0 = 0; g0 < num_grid_x; g0++)
{
grid_strides.push_back((GridAndStride){g0, g1, stride});
grid_and_strides.push_back((GridAndStride){g0, g1, stride});
}
}
}
return grid_and_strides;
}

static inline float intersection_area(const Object& a, const Object& b)
Expand Down Expand Up @@ -165,28 +167,22 @@ static void nms_sorted_bboxes(const std::vector<Object>& faceobjects, std::vecto

static void generate_yolox_proposals(std::vector<GridAndStride> grid_strides, float* feat_blob, float prob_threshold, std::vector<Object>& objects)
{

const int num_anchors = grid_strides.size();

auto num_anchors = grid_strides.size();
for (int anchor_idx = 0; anchor_idx < num_anchors; anchor_idx++)
{
const int grid0 = grid_strides[anchor_idx].grid0;
const int grid1 = grid_strides[anchor_idx].grid1;
const int stride = grid_strides[anchor_idx].stride;

const int basic_pos = anchor_idx * (NUM_CLASSES + 5);

// yolox/models/yolo_head.py decode logic
float x_center = (feat_blob[basic_pos+0] + grid0) * stride;
float y_center = (feat_blob[basic_pos+1] + grid1) * stride;
float w = exp(feat_blob[basic_pos+2]) * stride;
float h = exp(feat_blob[basic_pos+3]) * stride;
float x0 = x_center - w * 0.5f;
float y0 = y_center - h * 0.5f;

float box_objectness = feat_blob[basic_pos+4];
for (int class_idx = 0; class_idx < NUM_CLASSES; class_idx++)
{
auto grid0 = (float)grid_strides[anchor_idx].grid0;
auto grid1 = (float)grid_strides[anchor_idx].grid1;
auto stride = (float)grid_strides[anchor_idx].stride;
float x_center = (feat_blob[basic_pos+0] + grid0) * stride;
float y_center = (feat_blob[basic_pos+1] + grid1) * stride;
float w = exp(feat_blob[basic_pos+2]) * stride;
float h = exp(feat_blob[basic_pos+3]) * stride;
float x0 = x_center - w * 0.5f;
float y0 = y_center - h * 0.5f;
float box_cls_score = feat_blob[basic_pos + 5 + class_idx];
float box_prob = box_objectness * box_cls_score;
if (box_prob > prob_threshold)
Expand Down Expand Up @@ -228,10 +224,9 @@ float* blobFromImage(cv::Mat& img){


static void decode_outputs(float* prob, std::vector<Object>& objects, float scale, const int img_w, const int img_h) {
static std::vector<int> strides{8, 16, 32};
static std::vector<GridAndStride> grid_strides = generate_grids_and_stride(strides);
std::vector<Object> proposals;
std::vector<int> strides = {8, 16, 32};
std::vector<GridAndStride> grid_strides;
generate_grids_and_stride(strides, grid_strides);
generate_yolox_proposals(grid_strides, prob, BBOX_CONF_THRESH, proposals);
std::cout << "num of boxes before nms: " << proposals.size() << std::endl;

Expand All @@ -241,7 +236,7 @@ static void decode_outputs(float* prob, std::vector<Object>& objects, float scal
nms_sorted_bboxes(proposals, picked, NMS_THRESH);


int count = picked.size();
size_t count = picked.size();

std::cout << "num of boxes: " << count << std::endl;

Expand Down Expand Up @@ -397,11 +392,8 @@ static void draw_objects(const cv::Mat& bgr, const std::vector<Object>& objects,

int x = obj.rect.x;
int y = obj.rect.y + 1;
//int y = obj.rect.y - label_size.height - baseLine;
if (y > image.rows)
y = image.rows;
//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)),
txt_bk_color, -1);
Expand Down