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gstnvinfer_impl.cpp
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gstnvinfer_impl.cpp
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/**
* Copyright (c) 2019-2022, NVIDIA CORPORATION. All rights reserved.
*
* NVIDIA Corporation and its licensors retain all intellectual property
* and proprietary rights in and to this software, related documentation
* and any modifications thereto. Any use, reproduction, disclosure or
* distribution of this software and related documentation without an express
* license agreement from NVIDIA Corporation is strictly prohibited.
*
*/
#include <vector>
#include <sstream>
#include <cassert>
#include <string>
#include "gstnvinfer_impl.h"
#include "gstnvinfer.h"
#include "gstnvinfer_yaml_parser.h"
#include "gstnvinfer_property_parser.h"
GST_DEBUG_CATEGORY_EXTERN (gst_nvinfer_debug);
#define GST_CAT_DEFAULT gst_nvinfer_debug
using namespace nvdsinfer;
namespace gstnvinfer
{
void
LockGMutex::lock ()
{
assert (!locked);
if (!locked)
g_mutex_lock (&m);
locked = true;
}
void
LockGMutex::unlock ()
{
assert (locked);
if (locked)
g_mutex_unlock (&m);
locked = false;
}
void
LockGMutex::wait (GCond & cond)
{
assert (locked);
if (locked)
g_cond_wait (&cond, &m);
}
DsNvInferImpl::DsNvInferImpl (GstNvInfer * infer)
: m_InitParams (new NvDsInferContextInitParams),
m_GstInfer (infer)
{
NvDsInferContext_ResetInitParams (m_InitParams.get ());
}
DsNvInferImpl::~DsNvInferImpl ()
{
if (m_InitParams) {
delete[]m_InitParams->perClassDetectionParams;
g_strfreev (m_InitParams->outputLayerNames);
g_strfreev (m_InitParams->outputIOFormats);
g_strfreev (m_InitParams->layerDevicePrecisions);
}
}
/** Initialize the ModelLoadThread instance - start the model load thread. */
DsNvInferImpl::ModelLoadThread::ModelLoadThread (DsNvInferImpl & impl)
: m_Impl (impl)
{
m_Thread = std::thread (&DsNvInferImpl::ModelLoadThread::Run, this);
}
/** Destroy the ModelLoadThread instance - stop and join the model load thread. */
DsNvInferImpl::ModelLoadThread::~ModelLoadThread ()
{
if (m_Thread.joinable ()) {
//push stop signal
m_PendingModels.push (ModelItem ("", MODEL_LOAD_STOP));
m_Thread.join ();
}
m_PendingModels.clear ();
}
/** Callable function for the thread. */
void
DsNvInferImpl::ModelLoadThread::Run ()
{
while (true) {
/* Pop a pending model update item. This is a blocking call. */
ModelItem item = m_PendingModels.pop ();
std::string file;
ModelLoadType type;
std::tie (file, type) = item;
// receive thread stop signal
if (type == MODEL_LOAD_STOP)
break;
if (file.empty ())
continue;
// Load the new model
m_Impl.loadModel (file, type);
}
}
NvDsInferStatus
DsNvInferImpl::start ()
{
m_ModelLoadThread.reset (new ModelLoadThread (*this));
return NVDSINFER_SUCCESS;
}
void
DsNvInferImpl::stop ()
{
m_ModelLoadThread.reset ();
m_InferCtx.reset ();
}
/* Queue a new model update. */
bool
DsNvInferImpl::triggerNewModel (const std::string & modelPath,
ModelLoadType loadType)
{
if (!m_ModelLoadThread.get ()) {
return false;
}
m_ModelLoadThread->queueModel (modelPath, loadType);
return true;
}
/* Load the new model - Try to create a new NvDsInferContext instance with new
* parameters and store the instance in m_NextContextReplacement. */
void
DsNvInferImpl::loadModel (const std::string & modelPath, ModelLoadType loadType)
{
NvDsInferContextInitParams curParam;
bool needUpdate = true;
/* Check if a model is loaded but not yet being used for inferencing. */
{
LockGMutex lock (m_GstInfer->process_lock);
curParam = *m_InitParams;
needUpdate = !m_NextContextReplacement;
}
if (!needUpdate) {
notifyLoadModelStatus (ModelStatus {
NVDSINFER_UNKNOWN_ERROR, modelPath, "Trying to update model too frequently"}
);
return;
}
NvDsInferContextInitParamsPtr newParamsPtr (new NvDsInferContextInitParams);
NvDsInferContextInitParams & newParams = *newParamsPtr;
/* Initialize the NvDsInferContextInitParams struct with the new model
* config. */
if (!initNewInferModelParams (newParams, modelPath, loadType, curParam)) {
notifyLoadModelStatus (ModelStatus {
NVDSINFER_CONFIG_FAILED, modelPath,
"Initialization of new model params failed"}
);
return;
}
NvDsInferContextHandle newContext;
/* Create new NvDsInferContext instance. */
NvDsInferStatus err =
createNvDsInferContext (&newContext, newParams, m_GstInfer,
gst_nvinfer_logger);
if (err != NVDSINFER_SUCCESS) {
/* Notify application if the model load failed. */
notifyLoadModelStatus (ModelStatus {
err, modelPath, "Creation new model context failed"}
);
return;
}
NvDsInferContextPtr newCtxPtr (newContext);
assert (newCtxPtr.get ());
/* Check that the input of the newly loaded model parameter is compatible
* with gst-nvinfer instance. */
if (!isNewContextValid (*newCtxPtr, newParams)) {
notifyLoadModelStatus (ModelStatus {
NVDSINFER_CONFIG_FAILED, modelPath,
"New model's settings doesn't match current model"}
);
return;
}
/* Store the new NvDsInferContext instance so that it can be used for
* inferencing after ensuring synchronization with existing buffers
* being processed. */
if (!triggerContextReplace (newCtxPtr, std::move (newParamsPtr), modelPath)) {
notifyLoadModelStatus (ModelStatus {
NVDSINFER_UNKNOWN_ERROR, modelPath, "trigger new model replace failed"}
);
return;
}
}
/* Initialize NvDsInferContextInitParams with a combination of current
* init params and new init params for the new model. */
bool
DsNvInferImpl::initNewInferModelParams (NvDsInferContextInitParams & newParams,
const std::string & newModelPath, ModelLoadType loadType,
const NvDsInferContextInitParams & oldParams)
{
static const std::string string_yml = ".yml";
static const std::string string_yaml = ".yaml";
static const std::string string_txt = ".txt";
NvDsInferContext_ResetInitParams (&newParams);
assert (!newModelPath.empty ());
switch (loadType) {
case MODEL_LOAD_FROM_CONFIG:
if(!newModelPath.compare (newModelPath.length() - 4, 4, string_yml) ||
!newModelPath.compare (newModelPath.length() - 5, 5, string_yaml)) {
if (!gst_nvinfer_parse_context_params_yaml (&newParams, newModelPath.c_str ())) {
GST_WARNING_OBJECT (m_GstInfer,
"[UID %d]: parse new model config file: %s failed.",
m_GstInfer->unique_id, newModelPath.c_str ());
return false;
}
} else if (!newModelPath.compare (newModelPath.length() - 4, 4, string_txt)) {
if (!gst_nvinfer_parse_context_params (&newParams, newModelPath.c_str ())) {
GST_WARNING_OBJECT (m_GstInfer,
"[UID %d]: parse new model config file: %s failed.",
m_GstInfer->unique_id, newModelPath.c_str ());
return false;
}
}
break;
case MODEL_LOAD_FROM_ENGINE:
g_strlcpy (newParams.modelEngineFilePath, newModelPath.c_str (),
sizeof (newParams.modelEngineFilePath));
newParams.networkMode = oldParams.networkMode;
memcpy (newParams.meanImageFilePath, oldParams.meanImageFilePath,
sizeof (newParams.meanImageFilePath));
newParams.networkScaleFactor = oldParams.networkScaleFactor;
newParams.networkInputFormat = oldParams.networkInputFormat;
newParams.numOffsets = oldParams.numOffsets;
memcpy (newParams.offsets, oldParams.offsets, sizeof (newParams.offsets));
break;
default:
GST_WARNING_OBJECT (m_GstInfer,
"[UID %d]: unsupported model load type (:%s), internal error.",
m_GstInfer->unique_id, newModelPath.c_str ());
return false;
}
newParams.maxBatchSize = oldParams.maxBatchSize;
newParams.gpuID = oldParams.gpuID;
newParams.uniqueID = oldParams.uniqueID;
newParams.networkType = oldParams.networkType;
newParams.useDBScan = oldParams.useDBScan;
newParams.classifierThreshold = oldParams.classifierThreshold;
newParams.segmentationThreshold = oldParams.segmentationThreshold;
newParams.copyInputToHostBuffers = oldParams.copyInputToHostBuffers;
newParams.outputBufferPoolSize = oldParams.outputBufferPoolSize;
if (string_empty (newParams.labelsFilePath)
&& !string_empty (oldParams.labelsFilePath)) {
g_strlcpy (newParams.labelsFilePath, oldParams.labelsFilePath,
sizeof (newParams.labelsFilePath));
}
if (oldParams.numDetectedClasses) {
newParams.numDetectedClasses = oldParams.numDetectedClasses;
delete[]newParams.perClassDetectionParams;
newParams.perClassDetectionParams =
new NvDsInferDetectionParams[oldParams.numDetectedClasses];
memcpy (newParams.perClassDetectionParams,
oldParams.perClassDetectionParams,
sizeof (newParams.perClassDetectionParams[0]) *
newParams.numDetectedClasses);
}
return true;
}
/* Check that the input of the newly loaded model is compatible with
* gst-nvinfer instance. */
bool
DsNvInferImpl::isNewContextValid (INvDsInferContext & newCtx,
NvDsInferContextInitParams & newParam)
{
if (newParam.maxBatchSize < m_GstInfer->max_batch_size) {
GST_WARNING_OBJECT (m_GstInfer,
"[UID %d]: New model batch-size[in config] (%d) is smaller then gst-nvinfer's"
" configured batch-size (%d).", m_GstInfer->unique_id,
newParam.maxBatchSize, m_GstInfer->max_batch_size);
return false;
}
NvDsInferNetworkInfo networkInfo;
newCtx.getNetworkInfo (networkInfo);
if (m_GstInfer->network_width != (gint) networkInfo.width ||
m_GstInfer->network_height != (gint) networkInfo.height) {
GST_WARNING_OBJECT (m_GstInfer,
"[UID %d]: New model input resolution (%dx%d) is not compatible with "
"gst-nvinfer's current resolution (%dx%d).", m_GstInfer->unique_id,
networkInfo.width, networkInfo.height, m_GstInfer->network_width,
m_GstInfer->network_height);
return false;
}
return true;
}
/* Notify the app of model load status using GObject signal. */
void
DsNvInferImpl::notifyLoadModelStatus (const ModelStatus & res)
{
assert (!res.cfg_file.empty ());
if (res.status == NVDSINFER_SUCCESS) {
GST_INFO_OBJECT (m_GstInfer, "[UID %d]: Load new model:%s sucessfully",
m_GstInfer->unique_id, res.cfg_file.c_str ());
} else {
GST_ELEMENT_WARNING (m_GstInfer, LIBRARY, SETTINGS,
("[UID %d]: Load new model:%s failed, reason: %s",
m_GstInfer->unique_id, res.cfg_file.c_str (),
(res.message.empty ()? "unknown" : res.message.c_str ())),
(nullptr));
}
g_signal_emit (m_GstInfer, gst_nvinfer_signals[SIGNAL_MODEL_UPDATED], 0,
(int) res.status, res.cfg_file.c_str ());
}
bool
DsNvInferImpl::triggerContextReplace (NvDsInferContextPtr ctx,
NvDsInferContextInitParamsPtr params, const std::string & path)
{
std::string lastConfig;
LockGMutex lock (m_GstInfer->process_lock);
m_NextContextReplacement.reset (new ContextReplacementPtr::element_type (ctx,
std::move (params), path));
return true;
}
DsNvInferImpl::ContextReplacementPtr
DsNvInferImpl::getNextReplacementUnlock ()
{
if (!m_NextContextReplacement.get ()) {
return nullptr;
}
ContextReplacementPtr next;
// get next replacement, meanwhile empty m_NextContextReplacement
next.swap (m_NextContextReplacement);
return next;
}
/* Wait till all the buffers with gst-nvinfer are inferred/post-processed and
* pushed downstream. */
NvDsInferStatus
DsNvInferImpl::flushDataUnlock (LockGMutex & lock)
{
GstNvInferBatch *batch = new GstNvInferBatch;
batch->event_marker = TRUE;
/* Push the event marker batch to ensure all data processed. */
g_queue_push_tail (m_GstInfer->input_queue, batch);
g_cond_broadcast (&m_GstInfer->process_cond);
/* Wait till all the items in the two queues are handled. */
while (!g_queue_is_empty (m_GstInfer->input_queue)) {
lock.wait (m_GstInfer->process_cond);
}
while (!g_queue_is_empty (m_GstInfer->process_queue)) {
lock.wait (m_GstInfer->process_cond);
}
g_cond_broadcast (&m_GstInfer->process_cond);
for (auto & si:*(m_GstInfer->source_info)) {
si.second.object_history_map.clear ();
}
return NVDSINFER_SUCCESS;
}
/* Actually replace the current NvDsInferContext used for inferencing with
* the newly created NvDsInferContext. Also query updated information about
* the model. */
NvDsInferStatus
DsNvInferImpl::resetContextUnlock (NvDsInferContextPtr ctx,
NvDsInferContextInitParamsPtr params, const std::string & path)
{
assert (ctx.get () && params.get () && !path.empty ());
m_InferCtx = ctx;
m_InitParams = std::move (params);
GstNvInfer *nvinfer = m_GstInfer;
g_free (nvinfer->config_file_path);
nvinfer->config_file_path = g_strdup (path.c_str ());
/* Get the network resolution. */
ctx->getNetworkInfo (nvinfer->network_info);
nvinfer->network_width = nvinfer->network_info.width;
nvinfer->network_height = nvinfer->network_info.height;
/* Get information on all the bound layers. */
ctx->fillLayersInfo (*nvinfer->layers_info);
nvinfer->output_layers_info->clear ();
for (auto & layer:*(nvinfer->layers_info)) {
if (!layer.isInput)
nvinfer->output_layers_info->push_back (layer);
}
return NVDSINFER_SUCCESS;
}
/* Check if a new model has been loaded. If yes, ensure synchronization by
* waiting till all the queued buffers are processed and then do the actual
* model replacement. */
NvDsInferStatus
DsNvInferImpl::ensureReplaceNextContext ()
{
NvDsInferStatus err = NVDSINFER_SUCCESS;
LockGMutex lock (m_GstInfer->process_lock);
/* Get any newly loaded model. */
ContextReplacementPtr nextReplacement = getNextReplacementUnlock ();
if (!nextReplacement.get ())
return NVDSINFER_SUCCESS;
NvDsInferContextPtr nextCtx = std::get <0> (*nextReplacement);
NvDsInferContextInitParamsPtr nextParams;
nextParams.swap (std::get <1> (*nextReplacement));
assert (nextParams.get ());
const std::string path = std::get <2> (*nextReplacement);
/* Wait for current processing to finish. */
err = flushDataUnlock (lock);
if (err != NVDSINFER_SUCCESS) {
notifyLoadModelStatus (ModelStatus {
err, path, "Model update failed while flushing data"}
);
return err;
}
/* Replace the model to be used for inferencing. */
err = resetContextUnlock (nextCtx, std::move (nextParams), path);
if (err != NVDSINFER_SUCCESS) {
notifyLoadModelStatus (ModelStatus {
err, path, "Model update failed while replacing the current context"}
);
return err;
}
/* Notify application of successful model load. */
notifyLoadModelStatus (ModelStatus {
NVDSINFER_SUCCESS, path, "New Model updated succefully"}
);
return NVDSINFER_SUCCESS;
}
}