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https://gitlab.freedesktop.org/gstreamer/gstreamer.git
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1ff585233a
This element refactors functionality from gstonnxinference element, namely separating out the ONNX inference from the subsequent analysis. The new element runs an ONNX model on each video frame, and then attaches a TensorMeta meta with the output tensor data. This tensor data will then be consumed by downstream elements such as gstobjectdetector. At the moment, a provisional TensorMeta is used just in the ONNX plugin, but in future this will upgraded to a GStreamer API for other plugins to consume. Part-of: <https://gitlab.freedesktop.org/gstreamer/gstreamer/-/merge_requests/4916>
195 lines
6.2 KiB
C++
195 lines
6.2 KiB
C++
/*
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* GStreamer gstreamer-objectdetectorutils
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* Copyright (C) 2023 Collabora Ltd
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*
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* gstobjectdetectorutils.cpp
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*
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* This library is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Library General Public
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* License as published by the Free Software Foundation; either
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* version 2 of the License, or (at your option) any later version.
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*
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* This library 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 GNU
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* Library General Public License for more details.
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*
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* You should have received a copy of the GNU Library General Public
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* License along with this library; if not, write to the
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* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
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* Boston, MA 02110-1301, USA.
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*/
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#include "gstobjectdetectorutils.h"
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#include <fstream>
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#include "tensor/gsttensorid.h"
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GstMlBoundingBox::GstMlBoundingBox (std::string lbl, float score, float _x0,
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float _y0, float _width, float _height):
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label (lbl),
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score (score),
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x0 (_x0),
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y0 (_y0),
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width (_width),
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height (_height)
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{
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}
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GstMlBoundingBox::GstMlBoundingBox ():
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GstMlBoundingBox ("", 0.0f, 0.0f, 0.0f, 0.0f, 0.0f)
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{
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}
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namespace GstObjectDetectorUtils
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{
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GstObjectDetectorUtils::GstObjectDetectorUtils ()
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{
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}
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std::vector < std::string >
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GstObjectDetectorUtils::ReadLabels (const std::string & labelsFile)
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{
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std::vector < std::string > labels;
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std::string line;
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std::ifstream fp (labelsFile);
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while (std::getline (fp, line))
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labels.push_back (line);
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return labels;
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}
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std::vector < GstMlBoundingBox > GstObjectDetectorUtils::run (int32_t w,
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int32_t h, GstTensorMeta * tmeta, std::string labelPath,
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float scoreThreshold)
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{
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auto classIndex = gst_tensor_meta_get_index_from_id (tmeta,
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gst_tensorid_get_quark (GST_MODEL_OBJECT_DETECTOR_CLASSES));
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if (classIndex == GST_TENSOR_MISSING_ID) {
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GST_ERROR ("Missing class tensor id");
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return std::vector < GstMlBoundingBox > ();
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}
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auto type = tmeta->tensor[classIndex].type;
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return (type == GST_TENSOR_TYPE_FLOAT32) ?
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doRun < float >(w, h, tmeta, labelPath, scoreThreshold)
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: doRun < int >(w, h, tmeta, labelPath, scoreThreshold);
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}
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template < typename T > std::vector < GstMlBoundingBox >
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GstObjectDetectorUtils::doRun (int32_t w, int32_t h,
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GstTensorMeta * tmeta, std::string labelPath, float scoreThreshold)
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{
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std::vector < GstMlBoundingBox > boundingBoxes;
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GstMapInfo map_info[GstObjectDetectorMaxNodes];
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GstMemory *memory[GstObjectDetectorMaxNodes] = { NULL };
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std::vector < std::string > labels;
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gint index;
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T *numDetections = nullptr, *bboxes = nullptr, *scores =
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nullptr, *labelIndex = nullptr;
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// number of detections
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index = gst_tensor_meta_get_index_from_id (tmeta,
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gst_tensorid_get_quark (GST_MODEL_OBJECT_DETECTOR_NUM_DETECTIONS));
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if (index == GST_TENSOR_MISSING_ID) {
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GST_WARNING ("Missing tensor data for tensor index %d", index);
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goto cleanup;
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}
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memory[index] = gst_buffer_peek_memory (tmeta->tensor[index].data, 0);
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if (!memory[index]) {
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GST_WARNING ("Missing tensor data for tensor index %d", index);
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goto cleanup;
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}
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if (!gst_memory_map (memory[index], map_info + index, GST_MAP_READ)) {
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GST_WARNING ("Failed to map tensor memory for index %d", index);
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goto cleanup;
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}
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numDetections = (T *) map_info[index].data;
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// bounding boxes
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index =
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gst_tensor_meta_get_index_from_id (tmeta,
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gst_tensorid_get_quark (GST_MODEL_OBJECT_DETECTOR_BOXES));
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if (index == GST_TENSOR_MISSING_ID) {
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GST_WARNING ("Missing tensor data for tensor index %d", index);
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goto cleanup;
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}
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memory[index] = gst_buffer_peek_memory (tmeta->tensor[index].data, 0);
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if (!memory[index]) {
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GST_WARNING ("Failed to map tensor memory for index %d", index);
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goto cleanup;
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}
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if (!gst_memory_map (memory[index], map_info + index, GST_MAP_READ)) {
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GST_ERROR ("Failed to map GstMemory");
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goto cleanup;
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}
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bboxes = (T *) map_info[index].data;
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// scores
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index =
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gst_tensor_meta_get_index_from_id (tmeta,
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gst_tensorid_get_quark (GST_MODEL_OBJECT_DETECTOR_SCORES));
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if (index == GST_TENSOR_MISSING_ID) {
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GST_ERROR ("Missing scores tensor id");
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goto cleanup;
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}
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memory[index] = gst_buffer_peek_memory (tmeta->tensor[index].data, 0);
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if (!memory[index]) {
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GST_WARNING ("Missing tensor data for tensor index %d", index);
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goto cleanup;
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}
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if (!gst_memory_map (memory[index], map_info + index, GST_MAP_READ)) {
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GST_ERROR ("Failed to map GstMemory");
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goto cleanup;
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}
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scores = (T *) map_info[index].data;
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// optional label
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labelIndex = nullptr;
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index =
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gst_tensor_meta_get_index_from_id (tmeta,
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gst_tensorid_get_quark (GST_MODEL_OBJECT_DETECTOR_CLASSES));
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if (index != GST_TENSOR_MISSING_ID) {
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memory[index] = gst_buffer_peek_memory (tmeta->tensor[index].data, 0);
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if (!memory[index]) {
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GST_WARNING ("Missing tensor data for tensor index %d", index);
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goto cleanup;
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}
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if (!gst_memory_map (memory[index], map_info + index, GST_MAP_READ)) {
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GST_ERROR ("Failed to map GstMemory");
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goto cleanup;
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}
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labelIndex = (T *) map_info[index].data;
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}
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if (!labelPath.empty ())
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labels = ReadLabels (labelPath);
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for (int i = 0; i < numDetections[0]; ++i) {
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if (scores[i] > scoreThreshold) {
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std::string label = "";
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if (labelIndex && !labels.empty ())
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label = labels[labelIndex[i] - 1];
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auto score = scores[i];
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auto y0 = bboxes[i * 4] * h;
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auto x0 = bboxes[i * 4 + 1] * w;
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auto bheight = bboxes[i * 4 + 2] * h - y0;
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auto bwidth = bboxes[i * 4 + 3] * w - x0;
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boundingBoxes.push_back (GstMlBoundingBox (label, score, x0, y0, bwidth,
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bheight));
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}
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}
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cleanup:
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for (int i = 0; i < GstObjectDetectorMaxNodes; ++i) {
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if (memory[i])
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gst_memory_unmap (memory[i], map_info + i);
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}
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return boundingBoxes;
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}
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}
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