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Recator draw imprecise face

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This commit is contained in:
Barzan Hayati 2025-08-24 12:42:06 +00:00
parent 65b8f9b9a8
commit 3b9ff27524
2 changed files with 72 additions and 67 deletions
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137
src/nv_infer_server_manager.cpp
View File

@ -248,79 +248,82 @@ GstPadProbeReturn NvInferServerManager::pgie_pad_buffer_probe(
NvDsUserMeta *user_meta = (NvDsUserMeta *)l_user->data;
if (user_meta->base_meta.meta_type != NVDSINFER_TENSOR_OUTPUT_META)
continue;
/* convert to tensor metadata */
NvDsInferTensorMeta *meta =
(NvDsInferTensorMeta *)user_meta->user_meta_data;
for (unsigned int i = 0; i < meta->num_output_layers; i++) {
NvDsInferLayerInfo *info = &meta->output_layers_info[i];
info->buffer = meta->out_buf_ptrs_host[i];
if (use_device_mem && meta->out_buf_ptrs_dev[i]) {
cudaMemcpy(meta->out_buf_ptrs_host[i],
meta->out_buf_ptrs_dev[i],
info->inferDims.numElements * 4,
cudaMemcpyDeviceToHost);
}
}
/* Parse output tensor and fill detection results into objectList.
*/
std::vector<NvDsInferLayerInfo> outputLayersInfo(
meta->output_layers_info,
meta->output_layers_info + meta->num_output_layers);
#if NVDS_VERSION_MAJOR >= 5
if (nvds_lib_major_version >= 5) {
if (meta->network_info.width != networkInfo.width ||
meta->network_info.height != networkInfo.height ||
meta->network_info.channels != networkInfo.channels) {
g_error("failed to check pgie network info\n");
}
}
#endif
float *outputBuffer = (float *)outputLayersInfo[0].buffer;
(void)outputBuffer;
// NvDsInferDims dims = outputLayersInfo[0].inferDims;
for (size_t jkl = 0; jkl < outputLayersInfo.size(); jkl++) {
const NvDsInferLayerInfo &layer = outputLayersInfo[jkl];
unsigned int numDims = layer.inferDims.numDims;
unsigned int numElements = layer.inferDims.numElements;
(void)numElements;
(void)numDims;
// std::cout << "Layer " << jkl << " (" << layer.layerName <<
// "):\n"; std::cout << " Num Dims: " << numDims << "\n";
// std::cout << " Num Elements: " << numElements << "\n";
// std::cout << " Dims: [";
// for (unsigned int mno = 0; mno < numDims; ++mno) {
// std::cout << layer.inferDims.d[mno];
// // layer.inferDims.d[0] = 100;
// // layer.inferDims.d[1] = 57;
// if (mno < numDims - 1)
// std::cout << ", ";
// }
// std::cout << "]\n";
}
const NvDsInferLayerInfo &layer =
outputLayersInfo[0]; // or loop over all
uint detected_persons = 0;
float *data = static_cast<float *>(layer.buffer);
for (unsigned int jkl = 0; jkl < 100;
jkl++) { // 100 persons for each frame
if (data[jkl * 57 + 4] > threshold_body_detection) {
detected_persons++;
}
}
update_frame_with_face_body_meta(detected_persons, batch_meta, meta,
data, frame_meta);
extract_tensor_metadata(user_meta, networkInfo, batch_meta,
frame_meta);
}
}
// use_device_mem = 1 - use_device_mem;
return GST_PAD_PROBE_OK;
}
void NvInferServerManager::extract_tensor_metadata(
NvDsUserMeta *user_meta, NvDsInferNetworkInfo networkInfo,
NvDsBatchMeta *batch_meta, NvDsFrameMeta *frame_meta) {
/* convert to tensor metadata */
NvDsInferTensorMeta *meta =
(NvDsInferTensorMeta *)user_meta->user_meta_data;
for (unsigned int i = 0; i < meta->num_output_layers; i++) {
NvDsInferLayerInfo *info = &meta->output_layers_info[i];
info->buffer = meta->out_buf_ptrs_host[i];
if (use_device_mem && meta->out_buf_ptrs_dev[i]) {
cudaMemcpy(meta->out_buf_ptrs_host[i], meta->out_buf_ptrs_dev[i],
info->inferDims.numElements * 4, cudaMemcpyDeviceToHost);
}
}
/* Parse output tensor and fill detection results into objectList.
*/
std::vector<NvDsInferLayerInfo> outputLayersInfo(
meta->output_layers_info,
meta->output_layers_info + meta->num_output_layers);
#if NVDS_VERSION_MAJOR >= 5
if (nvds_lib_major_version >= 5) {
if (meta->network_info.width != networkInfo.width ||
meta->network_info.height != networkInfo.height ||
meta->network_info.channels != networkInfo.channels) {
g_error("failed to check pgie network info\n");
}
}
#endif
float *outputBuffer = (float *)outputLayersInfo[0].buffer;
(void)outputBuffer;
// NvDsInferDims dims = outputLayersInfo[0].inferDims;
for (size_t jkl = 0; jkl < outputLayersInfo.size(); jkl++) {
const NvDsInferLayerInfo &layer = outputLayersInfo[jkl];
unsigned int numDims = layer.inferDims.numDims;
unsigned int numElements = layer.inferDims.numElements;
(void)numElements;
(void)numDims;
// std::cout << "Layer " << jkl << " (" << layer.layerName <<
// "):\n"; std::cout << " Num Dims: " << numDims << "\n";
// std::cout << " Num Elements: " << numElements << "\n";
// std::cout << " Dims: [";
// for (unsigned int mno = 0; mno < numDims; ++mno) {
// std::cout << layer.inferDims.d[mno];
// // layer.inferDims.d[0] = 100;
// // layer.inferDims.d[1] = 57;
// if (mno < numDims - 1)
// std::cout << ", ";
// }
// std::cout << "]\n";
}
const NvDsInferLayerInfo &layer = outputLayersInfo[0]; // or loop over all
uint detected_persons = 0;
float *data = static_cast<float *>(layer.buffer);
for (unsigned int jkl = 0; jkl < 100;
jkl++) { // maximum 100 persons for each frame
if (data[jkl * 57 + 4] > threshold_body_detection) {
detected_persons++;
}
}
update_frame_with_face_body_meta(detected_persons, batch_meta, meta, data,
frame_meta);
}
void NvInferServerManager::update_frame_with_face_body_meta(
uint detected_persons, NvDsBatchMeta *batch_meta, NvDsInferTensorMeta *meta,
float *data, NvDsFrameMeta *frame_meta) {

2
src/nv_infer_server_manager.hpp
View File

@ -43,4 +43,6 @@ class NvInferServerManager {
static void update_frame_with_face_body_meta(uint, NvDsBatchMeta *,
NvDsInferTensorMeta *, float *,
NvDsFrameMeta *);
static void extract_tensor_metadata(NvDsUserMeta *, NvDsInferNetworkInfo,
NvDsBatchMeta *, NvDsFrameMeta *);
};