mirror of
https://github.com/Xaymar/obs-StreamFX
synced 2024-11-24 12:25:11 +00:00
237 lines
7.5 KiB
C++
237 lines
7.5 KiB
C++
/*
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* Modern effects for a modern Streamer
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* Copyright (C) 2020 Michael Fabian Dirks
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program; if not, write to the Free Software
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* Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA
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*/
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#include "nvidia-ar-facedetection.hpp"
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#include <algorithm>
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#include <stdexcept>
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#include "obs/gs/gs-helper.hpp"
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#include "util/util-logging.hpp"
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#ifdef _DEBUG
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#define ST_PREFIX "<%s> "
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#define D_LOG_ERROR(x, ...) P_LOG_ERROR(ST_PREFIX##x, __FUNCTION_SIG__, __VA_ARGS__)
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#define D_LOG_WARNING(x, ...) P_LOG_WARN(ST_PREFIX##x, __FUNCTION_SIG__, __VA_ARGS__)
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#define D_LOG_INFO(x, ...) P_LOG_INFO(ST_PREFIX##x, __FUNCTION_SIG__, __VA_ARGS__)
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#define D_LOG_DEBUG(x, ...) P_LOG_DEBUG(ST_PREFIX##x, __FUNCTION_SIG__, __VA_ARGS__)
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#else
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#define ST_PREFIX "<nvidia::ar::facedetection> "
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#define D_LOG_ERROR(...) P_LOG_ERROR(ST_PREFIX __VA_ARGS__)
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#define D_LOG_WARNING(...) P_LOG_WARN(ST_PREFIX __VA_ARGS__)
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#define D_LOG_INFO(...) P_LOG_INFO(ST_PREFIX __VA_ARGS__)
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#define D_LOG_DEBUG(...) P_LOG_DEBUG(ST_PREFIX __VA_ARGS__)
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#endif
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// At the current moment, both FaceDetection and FaceBoxDetection only support 8 faces.
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#define ST_MAX_TRACKED_FACES 8
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using namespace ::streamfx::nvidia;
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streamfx::nvidia::ar::facedetection::~facedetection()
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{
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D_LOG_DEBUG("Finalizing... (Addr: 0x%" PRIuPTR ")", this);
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}
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streamfx::nvidia::ar::facedetection::facedetection()
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: feature(FEATURE_FACE_DETECTION), _input(), _source(), _tmp(), _rects(), _rects_confidence(), _bboxes(),
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_dirty(true)
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{
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D_LOG_DEBUG("Initializing... (Addr: 0x%" PRIuPTR ")", this);
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// Assign CUDA Stream object.
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if (auto err = set(P_NVAR_CONFIG "CUDAStream", _nvcuda->get_stream()); err != cv::result::SUCCESS) {
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throw cv::exception("CUDAStream", err);
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}
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// Prepare initial memory
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_rects.resize(ST_MAX_TRACKED_FACES);
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_rects_confidence.resize(ST_MAX_TRACKED_FACES);
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// Set up initial configuration
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set_tracking_limit(1);
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// Attempt to load the feature.
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if (auto err = feature::load(); err != cv::result::SUCCESS) {
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throw cv::exception("Load", err);
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}
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}
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std::pair<size_t, size_t> ar::facedetection::tracking_limit_range()
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{
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return {1, ST_MAX_TRACKED_FACES};
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}
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size_t ar::facedetection::tracking_limit()
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{
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return _rects.size();
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}
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void ar::facedetection::set_tracking_limit(size_t v)
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{
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// Ensure there is always at least one face being tracked.
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v = std::max<size_t>(v, 1);
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// Resize all data.
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_rects.resize(v);
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_rects_confidence.resize(v);
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// Update bounding boxes structure.
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_bboxes.rects = _rects.data();
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_bboxes.maximum = v;
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_bboxes.current = 0;
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// Update feature.
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if (auto err = set_object(P_NVAR_OUTPUT "BoundingBoxes", reinterpret_cast<void*>(&_bboxes), sizeof(bounds_t));
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err != cv::result::SUCCESS) {
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throw cv::exception("BoundingBoxes", err);
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}
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if (auto err = set(P_NVAR_OUTPUT "BoundingBoxesConfidence", _rects_confidence); err != cv::result::SUCCESS) {
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throw cv::exception("BoundingBoxesConfidence", err);
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}
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if (auto err = set(P_NVAR_CONFIG "Temporal", (v == 1)); err != cv::result::SUCCESS) {
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throw cv::exception("Temporal", err);
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}
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// Mark effect dirty for reload.
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_dirty = true;
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}
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void ar::facedetection::process(std::shared_ptr<::streamfx::obs::gs::texture> in)
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{
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// Enter Graphics and CUDA context.
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auto gctx = ::streamfx::obs::gs::context();
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auto cctx = _nvcuda->get_context()->enter();
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#ifdef ENABLE_PROFILING
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::streamfx::obs::gs::debug_marker profiler1{::streamfx::obs::gs::debug_color_magenta, "NvAR Face Detection"};
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#endif
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// Resize if the size or scale was changed.
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resize(in->get_width(), in->get_height());
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// Reload effect if dirty.
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if (_dirty) {
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load();
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}
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{ // Copy parameter to input.
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#ifdef ENABLE_PROFILING
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::streamfx::obs::gs::debug_marker profiler1{::streamfx::obs::gs::debug_color_copy, "Copy In -> Input"};
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#endif
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gs_copy_texture(_input->get_texture()->get_object(), in->get_object());
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}
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{ // Convert Input to Source format
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#ifdef ENABLE_PROFILING
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::streamfx::obs::gs::debug_marker profiler1{::streamfx::obs::gs::debug_color_convert, "Copy Input -> Source"};
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#endif
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if (auto res = _nvcv->NvCVImage_Transfer(_input->get_image(), _source->get_image(), 1.f,
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_nvcuda->get_stream()->get(), _tmp->get_image());
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res != ::streamfx::nvidia::cv::result::SUCCESS) {
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D_LOG_ERROR("Failed to transfer input to processing source due to error: %s",
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_nvcv->NvCV_GetErrorStringFromCode(res));
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throw std::runtime_error("Transfer failed.");
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}
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}
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{ // Run
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#ifdef ENABLE_PROFILING
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::streamfx::obs::gs::debug_marker profiler1{::streamfx::obs::gs::debug_color_cache, "Run"};
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#endif
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if (auto err = run(); err != cv::result::SUCCESS) {
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throw cv::exception("Run", err);
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}
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}
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}
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size_t streamfx::nvidia::ar::facedetection::count()
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{
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return _bboxes.current;
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}
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streamfx::nvidia::ar::rect_t const& streamfx::nvidia::ar::facedetection::at(size_t index)
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{
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float v;
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return at(index, v);
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}
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streamfx::nvidia::ar::rect_t const& streamfx::nvidia::ar::facedetection::at(size_t index, float& confidence)
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{
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if (_bboxes.current == 0)
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throw std::runtime_error("no tracked faces");
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if (index > _bboxes.current)
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throw std::out_of_range("index too large");
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auto& ref = _rects.at(index);
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confidence = _rects_confidence.at(index);
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return ref;
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}
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void ar::facedetection::resize(uint32_t width, uint32_t height)
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{
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auto gctx = ::streamfx::obs::gs::context();
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auto cctx = ::streamfx::nvidia::cuda::obs::get()->get_context()->enter();
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if (!_tmp) {
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_tmp = std::make_shared<::streamfx::nvidia::cv::image>(
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width, height, ::streamfx::nvidia::cv::pixel_format::RGBA, ::streamfx::nvidia::cv::component_type::UINT8,
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::streamfx::nvidia::cv::component_layout::PLANAR, ::streamfx::nvidia::cv::memory_location::GPU, 1);
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}
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if (!_input || (width != _input->get_texture()->get_width()) || (height != _input->get_texture()->get_height())) {
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if (_input) {
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_input->resize(width, height);
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} else {
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_input = std::make_shared<::streamfx::nvidia::cv::texture>(width, height, GS_RGBA_UNORM);
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}
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_dirty = true;
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}
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if (!_source || (width != _source->get_image()->width) || (height != _source->get_image()->height)) {
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if (_source) {
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_source->resize(width, height);
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} else {
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_source = std::make_shared<::streamfx::nvidia::cv::image>(
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width, height, ::streamfx::nvidia::cv::pixel_format::BGR, ::streamfx::nvidia::cv::component_type::UINT8,
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::streamfx::nvidia::cv::component_layout::INTERLEAVED, ::streamfx::nvidia::cv::memory_location::GPU, 1);
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}
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if (auto err = set(P_NVAR_INPUT "Image", _source); err != cv::result::SUCCESS) {
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throw cv::exception("Image", err);
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}
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_dirty = true;
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}
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}
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void streamfx::nvidia::ar::facedetection::load()
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{
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auto gctx = ::streamfx::obs::gs::context();
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auto cctx = ::streamfx::nvidia::cuda::obs::get()->get_context()->enter();
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// Assign CUDA Stream object.
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if (auto err = set(P_NVAR_CONFIG "CUDAStream", _nvcuda->get_stream()); err != cv::result::SUCCESS) {
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throw cv::exception("CUDAStream", err);
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}
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// Attempt to load the feature.
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if (auto err = feature::load(); err != cv::result::SUCCESS) {
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throw cv::exception("Load", err);
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}
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_dirty = false;
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}
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