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filters/nv-face-tracking: Improve tracking and remove high priority CUDA stream

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The high priority CUDA stream causes libOBS to be at a lower priority than the tracking, which is not what we want. Instead we want tracking to be incomplete in those cases, rather than slowing down encoding and other things.

Geometry updates are also now done once per frame instead of one per tracking update, which should improve the smoothness without affecting performance too much. Additionally all tracking info is now in the 0..1 range, which drastically simplifies some math - especially with texture coordinates.

To deal with tracking and updates being asynchronous, a very simple approximation of movement velocity has been added. This is mostly wrong, but it can bridge the gap where tracking updates are slower, as the values are all filtered anyway.
This commit is contained in:
Michael Fabian 'Xaymar' Dirks 2020-05-09 23:40:17 +02:00 committed by Michael Fabian Dirks
parent ef283d219c
commit f111330f8e
3 changed files with 225 additions and 186 deletions
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2
data/locale/en-US.ini
View file

@ -221,7 +221,7 @@ Filter.DynamicMask.Channel.Input="%s Input Value"
Filter.DynamicMask.Channel.Input.Description="The input value for channel %s.\nSets 'value[%s][%s]' in the calculation 'mask[%s] = (base[%s] + value[%s][Red] * source[Red] + value[%s][Green] * source[Green] + value[%s][Blue] * source[Blue] + value[%s][Alpha] * source[Alpha]) * multiplier[%s]'."
# Filter - Nvidia Face Tracking
Filter.Nvidia.FaceTracking="Nvidia Face Tracking"
Filter.Nvidia.FaceTracking="NVIDIA Face Tracking"
Filter.Nvidia.FaceTracking.ROI="Region of Interest"
Filter.Nvidia.FaceTracking.ROI.Zoom="Zoom"
Filter.Nvidia.FaceTracking.ROI.Zoom.Description="Restrict the maximum zoom level based on the current maximum and minimum zoom level.\nValues above 100% zoom into the face, while values below 100% will keep their distance from the face."

361
source/filters/filter-nv-face-tracking.cpp
View file

@ -50,35 +50,17 @@ face_tracking_instance::face_tracking_instance(obs_data_t* settings, obs_source_
_rt_is_fresh(false), _rt(),
_cfg_roi_zoom(1.0), _cfg_roi_offset({0., 0.}), _cfg_roi_stability(1.0),
_cfg_zoom(1.0), _cfg_offset({0., 0.}), _cfg_stability(1.0),
_roi_center(), _roi_size(), _roi_geom(),
_geometry(), _filters(), _values(),
_cuda(face_tracking_factory::get()->get_cuda()), _cuda_ctx(face_tracking_factory::get()->get_cuda_context()),
_cuda_stream(),
_ar_library(face_tracking_factory::get()->get_ar()), _ar_loaded(false), _ar_feature(), _ar_tracked(true),
_ar_bboxes_data(), _ar_bboxes(), _ar_bboxes_confidence(),
_ar_texture(), _ar_texture_cuda_fresh(false), _ar_texture_cuda(), _ar_texture_cuda_mem(), _ar_image(),
_ar_image_bgr(), _ar_image_temp()
_ar_library(face_tracking_factory::get()->get_ar()), _ar_loaded(false), _ar_feature(), _ar_is_tracking(false),
_ar_bboxes_confidence(), _ar_bboxes_data(), _ar_bboxes(), _ar_texture(), _ar_texture_cuda_fresh(false),
_ar_texture_cuda(), _ar_texture_cuda_mem(), _ar_image(), _ar_image_bgr(), _ar_image_temp()
{
// Create Graphics resources for everything.
{
auto gctx = gs::context{};
_rt = std::make_shared<gs::rendertarget>(GS_RGBA, GS_ZS_NONE);
_roi_geom = std::make_shared<gs::vertex_buffer>(4, 1);
}
// Initialize everything.
{
auto cctx = std::make_shared<::nvidia::cuda::context_stack>(_cuda, _cuda_ctx);
std::int32_t minPrio, maxPrio;
_cuda->cuCtxGetStreamPriorityRange(&minPrio, &maxPrio);
_cuda_stream = std::make_shared<::nvidia::cuda::stream>(_cuda, ::nvidia::cuda::cu_stream_flags::NON_BLOCKING,
minPrio + ((maxPrio - minPrio) / 2));
}
#ifdef ENABLE_PROFILING
// Profiling
_profile_capture = util::profiler::create();
@ -91,12 +73,34 @@ face_tracking_instance::face_tracking_instance(obs_data_t* settings, obs_source_
_profile_ar_calc = util::profiler::create();
#endif
// Asynchronously load Face Tracking.
async_initialize(nullptr);
{ // Create render target, vertex buffer, and CUDA stream.
auto gctx = gs::context{};
_rt = std::make_shared<gs::rendertarget>(GS_RGBA, GS_ZS_NONE);
_geometry = std::make_shared<gs::vertex_buffer>(4, 1);
auto cctx = std::make_shared<::nvidia::cuda::context_stack>(_cuda, _cuda_ctx);
_cuda_stream =
std::make_shared<::nvidia::cuda::stream>(_cuda, ::nvidia::cuda::cu_stream_flags::NON_BLOCKING, 0);
}
{ // Asynchronously load Face Tracking.
async_initialize();
}
{ // Set up initial tracking data.
_values.center[0] = _values.center[1] = .5;
_values.size[0] = _values.size[1] = 1.;
refresh_region_of_interest();
}
}
face_tracking_instance::~face_tracking_instance()
{
// Kill pending tasks.
streamfx::threadpool()->pop(_async_initialize);
streamfx::threadpool()->pop(_async_track);
_ar_loaded.store(false);
std::unique_lock<std::mutex> alk{_ar_lock};
_ar_library->image_dealloc(&_ar_image_temp);
_ar_library->image_dealloc(&_ar_image_bgr);
}
@ -114,21 +118,23 @@ void face_tracking_instance::async_initialize(std::shared_ptr<void> ptr)
data->source =
std::shared_ptr<obs_weak_source_t>(obs_source_get_weak_source(_self), obs::obs_weak_source_deleter);
std::filesystem::path models_path = _ar_library->get_ar_sdk_path();
models_path = models_path.append("models");
models_path = std::filesystem::absolute(models_path);
models_path.concat("\\");
data->models_path = models_path.string();
{
std::filesystem::path models_path = _ar_library->get_ar_sdk_path();
models_path = models_path.append("models");
models_path = std::filesystem::absolute(models_path);
models_path.concat("\\");
data->models_path = models_path.string();
}
streamfx::threadpool()->push(std::bind(&face_tracking_instance::async_initialize, this, std::placeholders::_1),
data);
_async_initialize = streamfx::threadpool()->push(
std::bind(&face_tracking_instance::async_initialize, this, std::placeholders::_1), data);
} else {
std::shared_ptr<async_data> data = std::static_pointer_cast<async_data>(ptr);
// Try and acquire a strong source reference.
std::shared_ptr<obs_source_t> ref =
std::shared_ptr<obs_source_t> remote_work =
std::shared_ptr<obs_source_t>(obs_weak_source_get_source(data->source.get()), obs::obs_source_deleter);
if (!ref) { // If that failed, the source we are working for was deleted - abort now.
if (!remote_work) { // If that failed, the source we are working for was deleted - abort now.
return;
}
@ -162,7 +168,7 @@ void face_tracking_instance::async_initialize(std::shared_ptr<void> ptr)
// Finally enable Temporal tracking if possible.
if (NvCV_Status res = _ar_library->set_uint32(_ar_feature.get(), NvAR_Parameter_Config(Temporal), 1);
res != NVCV_SUCCESS) {
LOG_WARNING("<%s> Unable to enable Temporal tracking mode.", obs_source_get_name(ref.get()));
LOG_WARNING("<%s> Unable to enable Temporal tracking mode.", obs_source_get_name(remote_work.get()));
}
// Create Bounding Boxes Data
@ -191,55 +197,32 @@ void face_tracking_instance::async_initialize(std::shared_ptr<void> ptr)
} else {
_ar_loaded = true;
}
_async_initialize.reset();
}
}
void face_tracking_instance::refresh_geometry()
{ // Update Region of Interest Geometry.
std::unique_lock<std::mutex> lock(_roi_lock);
auto v0 = _roi_geom->at(0);
auto v1 = _roi_geom->at(1);
auto v2 = _roi_geom->at(2);
auto v3 = _roi_geom->at(3);
*v0.color = 0xFFFFFFFF;
*v1.color = 0xFFFFFFFF;
*v2.color = 0xFFFFFFFF;
*v3.color = 0xFFFFFFFF;
vec3_set(v3.position, static_cast<float_t>(_size.first), static_cast<float_t>(_size.second), 0.);
vec3_set(v2.position, v3.position->x, 0., 0.);
vec3_set(v1.position, 0., v3.position->y, 0.);
vec3_set(v0.position, 0., 0., 0.);
vec4_set(v0.uv[0],
static_cast<float_t>((_roi_center.first - _roi_size.first / 2.) / static_cast<double_t>(_size.first)),
static_cast<float_t>((_roi_center.second - _roi_size.second / 2.) / static_cast<double_t>(_size.second)),
0., 0.);
vec4_set(v1.uv[0],
static_cast<float_t>((_roi_center.first - _roi_size.first / 2.) / static_cast<double_t>(_size.first)),
static_cast<float_t>((_roi_center.second + _roi_size.second / 2.) / static_cast<double_t>(_size.second)),
0., 0.);
vec4_set(v2.uv[0],
static_cast<float_t>((_roi_center.first + _roi_size.first / 2.) / static_cast<double_t>(_size.first)),
static_cast<float_t>((_roi_center.second - _roi_size.second / 2.) / static_cast<double_t>(_size.second)),
0., 0.);
vec4_set(v3.uv[0],
static_cast<float_t>((_roi_center.first + _roi_size.first / 2.) / static_cast<double_t>(_size.first)),
static_cast<float_t>((_roi_center.second + _roi_size.second / 2.) / static_cast<double_t>(_size.second)),
0., 0.);
_roi_geom->update();
}
void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
{
struct async_data {
std::shared_ptr<obs_weak_source_t> source;
};
if (!_ar_loaded)
return;
if (!ptr) {
// Check if we can track.
if (_ar_is_tracking)
return; // Can't track a new frame right now.
#ifdef ENABLE_PROFILING
gs::debug_marker gdm{gs::debug_color_convert, "Start Asynchronous Tracking"};
#endif
// Don't push additional tracking frames while processing one.
_ar_is_tracking = true;
// Spawn the work for the threadpool.
std::shared_ptr<async_data> data = std::make_shared<async_data>();
data->source =
@ -251,7 +234,6 @@ void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
auto prof = _profile_capture_realloc->track();
gs::debug_marker marker{gs::debug_color_allocate, "Reallocate GPU Buffer"};
#endif
_ar_texture =
std::make_shared<gs::texture>(_size.first, _size.second, GS_RGBA, 1, nullptr, gs::texture::flags::None);
_ar_texture_cuda_fresh = false;
@ -262,25 +244,28 @@ void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
auto prof = _profile_capture_copy->track();
gs::debug_marker marker{gs::debug_color_copy, "Copy Capture", obs_source_get_name(_self)};
#endif
gs_copy_texture(_ar_texture->get_object(), _rt->get_texture()->get_object());
}
// Push work
streamfx::threadpool()->push(std::bind(&face_tracking_instance::async_track, this, std::placeholders::_1),
data);
_async_track = streamfx::threadpool()->push(
std::bind(&face_tracking_instance::async_track, this, std::placeholders::_1), data);
} else {
std::shared_ptr<async_data> data = std::static_pointer_cast<async_data>(ptr);
// Prevent conflicts.
std::unique_lock<std::mutex> alk{_ar_lock};
if (!_ar_loaded)
return;
// Try and acquire a strong source reference.
std::shared_ptr<obs_source_t> ref =
std::shared_ptr<async_data> data = std::static_pointer_cast<async_data>(ptr);
std::shared_ptr<obs_source_t> remote_work =
std::shared_ptr<obs_source_t>(obs_weak_source_get_source(data->source.get()), obs::obs_source_deleter);
if (!ref) { // If that failed, the source we are working for was deleted - abort now.
if (!remote_work) { // If that failed, the source we are working for was deleted - abort now.
return;
}
// Acquire GS context.
gs::context gctx;
gs::context gctx{};
// Update the current CUDA context for working.
auto cctx = std::make_shared<::nvidia::cuda::context_stack>(_cuda, _cuda_ctx);
@ -292,22 +277,23 @@ void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
gs::debug_marker marker{gs::debug_color_allocate, "%s: Reallocate CUDA Buffers",
obs_source_get_name(_self)};
#endif
// Assign new texture and allocate new memory.
std::size_t pitch = _size.first * 4ul;
std::size_t pitch = _ar_texture->get_width() * 4ul;
_ar_texture_cuda = std::make_shared<::nvidia::cuda::gstexture>(_cuda, _ar_texture);
_ar_texture_cuda_mem = std::make_shared<::nvidia::cuda::memory>(_cuda, pitch * _size.second);
_ar_library->image_init(&_ar_image, static_cast<unsigned int>(_size.first),
static_cast<unsigned int>(_size.second), static_cast<int>(pitch),
_ar_texture_cuda_mem = std::make_shared<::nvidia::cuda::memory>(_cuda, pitch * _ar_texture->get_height());
_ar_library->image_init(&_ar_image, static_cast<unsigned int>(_ar_texture->get_width()),
static_cast<unsigned int>(_ar_texture->get_height()), static_cast<int>(pitch),
reinterpret_cast<void*>(_ar_texture_cuda_mem->get()), NVCV_RGBA, NVCV_U8,
NVCV_INTERLEAVED, NVCV_CUDA);
// Reallocate transposed buffer.
_ar_library->image_dealloc(&_ar_image_bgr);
_ar_library->image_alloc(&_ar_image_bgr, static_cast<unsigned int>(_size.first),
static_cast<unsigned int>(_size.second), NVCV_BGR, NVCV_U8, NVCV_INTERLEAVED,
NVCV_CUDA, 0);
_ar_library->image_dealloc(&_ar_image_temp);
_ar_library->image_dealloc(&_ar_image_bgr);
_ar_library->image_alloc(&_ar_image_bgr, _ar_image.width, _ar_image.height, NVCV_BGR, NVCV_U8,
NVCV_INTERLEAVED, NVCV_CUDA, 0);
// Synchronize Streams.
_cuda->cuStreamSynchronize(_cuda_stream->get());
// Finally set the input object.
if (NvCV_Status res = _ar_library->set_object(_ar_feature.get(), NvAR_Parameter_Input(Image),
@ -325,7 +311,6 @@ void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
#ifdef ENABLE_PROFILING
auto prof = _profile_ar_copy->track();
#endif
::nvidia::cuda::cu_memcpy2d_t mc;
mc.src_x_in_bytes = 0;
mc.src_y = 0;
@ -344,7 +329,8 @@ void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
mc.width_in_bytes = static_cast<size_t>(_ar_image.pitch);
mc.height = _ar_image.height;
if (::nvidia::cuda::cu_result res = _cuda->cuMemcpy2D(&mc); res != ::nvidia::cuda::cu_result::SUCCESS) {
if (::nvidia::cuda::cu_result res = _cuda->cuMemcpy2DAsync(&mc, _cuda_stream->get());
res != ::nvidia::cuda::cu_result::SUCCESS) {
LOG_ERROR("<%s> Failed to prepare buffers for tracking.", obs_source_get_name(_self));
return;
}
@ -354,7 +340,6 @@ void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
#ifdef ENABLE_PROFILING
auto prof = _profile_ar_transfer->track();
#endif
if (NvCV_Status res =
_ar_library->image_transfer(&_ar_image, &_ar_image_bgr, 1.0,
reinterpret_cast<CUstream_st*>(_cuda_stream->get()), &_ar_image_temp);
@ -362,90 +347,128 @@ void face_tracking_instance::async_track(std::shared_ptr<void> ptr)
LOG_ERROR("<%s> Failed to convert from RGBX 32-bit to BGR 24-bit.", obs_source_get_name(_self));
return;
}
// Synchronize Streams.
_cuda->cuStreamSynchronize(_cuda_stream->get());
_cuda->cuCtxSynchronize();
}
{ // Track any faces.
#ifdef ENABLE_PROFILING
auto prof = _profile_ar_run->track();
#endif
if (NvCV_Status res = _ar_library->run(_ar_feature.get()); res != NVCV_SUCCESS) {
LOG_ERROR("<%s> Failed to run tracking.", obs_source_get_name(_self));
return;
}
}
if ((_ar_bboxes.num_boxes == 0) || (_ar_bboxes_confidence.at(0) < 0.5)) {
// Not confident enough or not tracking anything, return to full frame after a bit.
// Are we tracking anything, and confident enough in the tracking?
if ((_ar_bboxes.num_boxes == 0) || (_ar_bboxes_confidence.at(0) < 0.3333)) {
// If not, just return to full frame.
std::unique_lock<std::mutex> tlk{_values.lock};
_values.center[0] = .5;
_values.center[1] = .5;
_values.size[0] = 1.;
_values.size[1] = 1.;
_values.velocity[0] = 0;
_values.velocity[1] = 0;
} else {
// If yes, begin tracking.
#ifdef ENABLE_PROFILING
auto prof = _profile_ar_calc->track();
#endif
double_t aspect = double_t(_size.first) / double_t(_size.second);
double_t sx = static_cast<double_t>(_ar_image_bgr.width);
double_t sy = static_cast<double_t>(_ar_image_bgr.height);
double_t aspect = double_t(sx) / double_t(sy);
double_t fps = 0.;
{
obs_video_info ovi;
obs_get_video_info(&ovi);
fps = static_cast<double_t>(ovi.fps_num) / static_cast<double_t>(ovi.fps_den);
}
// Store values and center.
double_t bbox_w = _ar_bboxes.boxes[0].width;
double_t bbox_h = _ar_bboxes.boxes[0].height;
double_t bbox_cx = _ar_bboxes.boxes[0].x + bbox_w / 2.0;
double_t bbox_cy = _ar_bboxes.boxes[0].y + bbox_h / 2.0;
double_t bsx = _ar_bboxes.boxes[0].width;
double_t bsy = _ar_bboxes.boxes[0].height;
double_t bcx = _ar_bboxes.boxes[0].x + bsx / 2.0;
double_t bcy = _ar_bboxes.boxes[0].y + bsy / 2.0;
// Zoom, Aspect Ratio, Offset
bbox_h = util::math::lerp<double_t>(_size.second, bbox_h, _cfg_roi_zoom);
bbox_h = std::clamp(bbox_h, 10 * aspect, static_cast<double_t>(_size.second));
bbox_w = bbox_h * aspect;
bbox_cx += _ar_bboxes.boxes[0].width * _cfg_roi_offset.first;
bbox_cy += _ar_bboxes.boxes[0].height * _cfg_roi_offset.second;
bsy = util::math::lerp<double_t>(sy, bsy, _cfg_zoom);
bsy = std::clamp(bsy, 10 * aspect, static_cast<double_t>(_size.second));
bsx = bsy * aspect;
bcx += _ar_bboxes.boxes[0].width * _cfg_offset.first;
bcy += _ar_bboxes.boxes[0].height * _cfg_offset.second;
// Fit back into the frame
// - Above code guarantees that height is never bigger than the height of the frame.
// - Which also guarantees that width is never bigger than the width of the frame.
// Only cx and cy need to be adjusted now to always be in the frame.
bbox_cx = std::clamp(bbox_cx, (bbox_w / 2.), static_cast<double_t>(_size.first) - (bbox_w / 2.));
bbox_cy = std::clamp(bbox_cy, (bbox_h / 2.), static_cast<double_t>(_size.second) - (bbox_h / 2.));
bcx = std::clamp(bcx, (bsx / 2.), sx - (bsx / 2.));
bcy = std::clamp(bcy, (bsy / 2.), sy - (bsy / 2.));
// Filter values
auto size_w = _roi_filters[2].filter(bbox_w);
auto size_h = _roi_filters[3].filter(bbox_h);
auto center_x = _roi_filters[0].filter(bbox_cx);
auto center_y = _roi_filters[1].filter(bbox_cy);
// Fix NaN/Infinity
if (std::isfinite(size_w) && std::isfinite(size_h) && std::isfinite(center_x) && std::isfinite(center_y)) {
std::unique_lock<std::mutex> lock(_roi_lock);
_roi_center.first = center_x;
_roi_center.second = center_y;
_roi_size.first = size_w;
_roi_size.second = size_h;
} else {
std::unique_lock<std::mutex> lock(_roi_lock);
roi_refresh();
{ // Update target values.
std::unique_lock<std::mutex> tlk{_values.lock};
_values.velocity[0] = -_values.center[0];
_values.velocity[1] = -_values.center[1];
_values.center[0] = bcx / sx;
_values.center[1] = bcy / sy;
_values.velocity[0] += _values.center[0];
_values.velocity[1] += _values.center[1];
_values.velocity[0] *= fps;
_values.velocity[1] *= fps;
_values.size[0] = bsx / sx;
_values.size[1] = bsy / sy;
}
}
_ar_tracked = true;
_async_track.reset();
// Allow new frames to be queued again.
_ar_is_tracking = false;
}
}
void face_tracking_instance::roi_refresh()
{
double_t kalman_q = util::math::lerp<double_t>(1.0, 1e-6, _cfg_roi_stability);
double_t kalman_r = util::math::lerp<double_t>(std::numeric_limits<double_t>::epsilon(), 1e+2, _cfg_roi_stability);
void face_tracking_instance::refresh_geometry()
{ // Update Region of Interest Geometry.
auto v0 = _geometry->at(0);
auto v1 = _geometry->at(1);
auto v2 = _geometry->at(2);
auto v3 = _geometry->at(3);
_roi_filters[0] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1.0, _roi_center.first};
_roi_filters[1] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1.0, _roi_center.second};
_roi_filters[2] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1.0, _roi_size.first};
_roi_filters[3] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1.0, _roi_size.second};
vec3_set(v3.position, static_cast<float_t>(_size.first), static_cast<float_t>(_size.second), 0.);
vec3_set(v2.position, v3.position->x, 0., 0.);
vec3_set(v1.position, 0., v3.position->y, 0.);
vec3_set(v0.position, 0., 0., 0.);
float_t hsx = static_cast<float_t>(_filters.size[0].get() / 2.);
float_t hsy = static_cast<float_t>(_filters.size[1].get() / 2.);
vec4_set(v0.uv[0], static_cast<float_t>(_filters.center[0].get() - hsx),
static_cast<float_t>(_filters.center[1].get() - hsy), 0., 0.);
vec4_set(v1.uv[0], static_cast<float_t>(_filters.center[0].get() - hsx),
static_cast<float_t>(_filters.center[1].get() + hsy), 0., 0.);
vec4_set(v2.uv[0], static_cast<float_t>(_filters.center[0].get() + hsx),
static_cast<float_t>(_filters.center[1].get() - hsy), 0., 0.);
vec4_set(v3.uv[0], static_cast<float_t>(_filters.center[0].get() + hsx),
static_cast<float_t>(_filters.center[1].get() + hsy), 0., 0.);
_geometry->update(true);
}
void face_tracking_instance::roi_reset()
void face_tracking_instance::refresh_region_of_interest()
{
_roi_center.first = static_cast<double_t>(_size.first / 2);
_roi_center.second = static_cast<double_t>(_size.second / 2);
_roi_size.first = static_cast<double_t>(_size.first);
_roi_size.second = static_cast<double_t>(_size.second);
std::unique_lock<std::mutex> tlk(_values.lock);
roi_refresh();
double_t kalman_q = util::math::lerp<double_t>(1.0, 1e-6, _cfg_stability);
double_t kalman_r = util::math::lerp<double_t>(std::numeric_limits<double_t>::epsilon(), 1e+2, _cfg_stability);
_filters.center[0] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1., _values.center[0]};
_filters.center[1] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1., _values.center[1]};
_filters.size[0] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1., _values.size[0]};
_filters.size[1] = util::math::kalman1D<double_t>{kalman_q, kalman_r, 1., _values.size[1]};
}
void face_tracking_instance::load(obs_data_t* data)
@ -457,14 +480,13 @@ void face_tracking_instance::migrate(obs_data_t* data, std::uint64_t version) {}
void face_tracking_instance::update(obs_data_t* data)
{
_cfg_roi_zoom = obs_data_get_double(data, SK_ROI_ZOOM) / 100.0;
_cfg_roi_offset.first = obs_data_get_double(data, SK_ROI_OFFSET_X) / 100.0;
_cfg_roi_offset.second = obs_data_get_double(data, SK_ROI_OFFSET_Y) / 100.0;
_cfg_roi_stability = obs_data_get_double(data, SK_ROI_STABILITY) / 100.0;
_cfg_zoom = obs_data_get_double(data, SK_ROI_ZOOM) / 100.0;
_cfg_offset.first = obs_data_get_double(data, SK_ROI_OFFSET_X) / 100.0;
_cfg_offset.second = obs_data_get_double(data, SK_ROI_OFFSET_Y) / 100.0;
_cfg_stability = obs_data_get_double(data, SK_ROI_STABILITY) / 100.0;
// Refresh the Region Of Interest
std::unique_lock<std::mutex> lock(_roi_lock);
roi_refresh();
refresh_region_of_interest();
}
void face_tracking_instance::video_tick(float_t seconds)
@ -474,11 +496,24 @@ void face_tracking_instance::video_tick(float_t seconds)
return;
}
if (obs_source_t* target = obs_filter_get_target(_self); target != nullptr) {
_size.first = obs_source_get_width(target);
_size.second = obs_source_get_height(target);
// Update the input size.
if (obs_source_t* src = obs_filter_get_target(_self); src != nullptr) {
_size.first = obs_source_get_base_width(src);
_size.second = obs_source_get_base_height(src);
}
// Update filters and geometry
{
std::unique_lock<std::mutex> tlk(_values.lock);
_filters.center[0].filter(_values.center[0]);
_filters.center[1].filter(_values.center[1]);
_filters.size[0].filter(_values.size[0]);
_filters.size[1].filter(_values.size[1]);
_values.center[0] += _values.velocity[0] * seconds;
_values.center[1] += _values.velocity[1] * seconds;
}
refresh_geometry();
_rt_is_fresh = false;
}
@ -494,8 +529,8 @@ void face_tracking_instance::video_render(gs_effect_t* effect)
}
#ifdef ENABLE_PROFILING
gs::debug_marker gdmp{gs::debug_color_source, "Nvidia Face Tracking '%s' on '%s'", obs_source_get_name(_self),
obs_source_get_name(obs_filter_get_parent(_self))};
gs::debug_marker gdmp{gs::debug_color_source, "NVIDIA Face Tracking '%s'...", obs_source_get_name(_self)};
gs::debug_marker gdmp2{gs::debug_color_source, "... on '%s'", obs_source_get_name(obs_filter_get_parent(_self))};
#endif
if (!_rt_is_fresh) { // Capture the filter stack "below" us.
@ -512,24 +547,20 @@ void face_tracking_instance::video_render(gs_effect_t* effect)
auto op = _rt->render(_size.first, _size.second);
vec4 clr = {0., 0., 0., 0.};
gs_ortho(0., static_cast<float_t>(_size.first), 0., static_cast<float_t>(_size.second), 0., 1.);
gs_clear(GS_CLEAR_COLOR, &clr, 0., 0.);
gs_ortho(0., 1., 0., 1., -1., 1.);
gs_clear(GS_CLEAR_COLOR, &clr, 0., 0);
gs_enable_color(true, true, true, true);
gs_enable_blending(false);
obs_source_process_filter_tech_end(_self, default_effect, _size.first, _size.second, "Draw");
obs_source_process_filter_tech_end(_self, default_effect, 1, 1, "Draw");
} else {
obs_source_skip_video_filter(_self);
return;
}
}
if (_ar_tracked) {
#ifdef ENABLE_PROFILING
gs::debug_marker gdm{gs::debug_color_convert, "Trigger Async Tracking Task"};
#endif
async_track(nullptr);
refresh_geometry();
}
// Probably spawn new work.
async_track(nullptr);
_rt_is_fresh = true;
}
@ -541,9 +572,9 @@ void face_tracking_instance::video_render(gs_effect_t* effect)
gs_effect_set_texture(gs_effect_get_param_by_name(effect ? effect : default_effect, "image"),
_rt->get_texture()->get_object());
gs_load_vertexbuffer(_roi_geom->update());
gs_load_vertexbuffer(_geometry->update(false));
while (gs_effect_loop(effect ? effect : default_effect, "Draw")) {
gs_draw(gs_draw_mode::GS_TRISTRIP, 0, _roi_geom->size());
gs_draw(gs_draw_mode::GS_TRISTRIP, 0, 0);
}
gs_load_vertexbuffer(nullptr);
}
@ -690,7 +721,7 @@ void streamfx::filter::nvidia::face_tracking_factory::initialize()
try {
_filter_nvidia_face_tracking_factory_instance = std::make_shared<filter::nvidia::face_tracking_factory>();
} catch (const std::exception& ex) {
LOG_ERROR("<Nvidia Face Tracking Filter> %s", ex.what());
LOG_ERROR("<NVIDIA Face Tracking Filter> %s", ex.what());
}
}

48
source/filters/filter-nv-face-tracking.hpp
View file

@ -37,21 +37,29 @@
namespace streamfx::filter::nvidia {
class face_tracking_instance : public obs::source_instance {
// Filter Cache
std::pair<std::uint32_t, std::uint32_t> _size;
bool _rt_is_fresh;
std::shared_ptr<gs::rendertarget> _rt;
std::pair<std::uint32_t, std::uint32_t> _size;
std::mutex _delete_protection;
// Settings
double_t _cfg_roi_zoom;
std::pair<double_t, double_t> _cfg_roi_offset;
double_t _cfg_roi_stability;
double_t _cfg_zoom;
std::pair<double_t, double_t> _cfg_offset;
double_t _cfg_stability;
// Region of Interest
util::math::kalman1D<double_t> _roi_filters[4];
std::mutex _roi_lock;
std::pair<double_t, double_t> _roi_center;
std::pair<double_t, double_t> _roi_size;
std::shared_ptr<gs::vertex_buffer> _roi_geom;
// Operational Data
std::shared_ptr<gs::vertex_buffer> _geometry;
struct {
util::math::kalman1D<double_t> center[2];
util::math::kalman1D<double_t> size[2];
} _filters;
struct {
std::mutex lock;
double_t center[2];
double_t size[2];
double_t velocity[2];
} _values;
// Nvidia CUDA interop
std::shared_ptr<::nvidia::cuda::cuda> _cuda;
@ -62,7 +70,8 @@ namespace streamfx::filter::nvidia {
std::shared_ptr<::nvidia::ar::ar> _ar_library;
std::atomic_bool _ar_loaded;
std::shared_ptr<nvAR_Feature> _ar_feature;
std::atomic_bool _ar_tracked;
std::atomic_bool _ar_is_tracking;
std::mutex _ar_lock;
std::vector<float_t> _ar_bboxes_confidence;
std::vector<NvAR_Rect> _ar_bboxes_data;
NvAR_BBoxes _ar_bboxes;
@ -74,6 +83,10 @@ namespace streamfx::filter::nvidia {
NvCVImage _ar_image_bgr;
NvCVImage _ar_image_temp;
// Tasks
std::shared_ptr<::util::threadpool::task> _async_initialize;
std::shared_ptr<::util::threadpool::task> _async_track;
#ifdef ENABLE_PROFILING
// Profiling
std::shared_ptr<util::profiler> _profile_capture;
@ -91,18 +104,13 @@ namespace streamfx::filter::nvidia {
virtual ~face_tracking_instance() override;
// Tasks
void async_initialize(std::shared_ptr<void>);
void async_initialize(std::shared_ptr<void> = nullptr);
void async_track(std::shared_ptr<void> = nullptr);
void refresh_geometry();
void async_track(std::shared_ptr<void>);
// Create image buffer.
//void create_image_buffer(std::size_t width, std::size_t height);
void roi_refresh();
void roi_reset();
void refresh_region_of_interest();
virtual void load(obs_data_t* data) override;