Deepstream back to back detectors with DashCamNetand VehicleMakeNet not classifying correctly - nvidia-deepstream

Question

Question also posted on their forum here: https://forums.developer.nvidia.com/t/deepstream-back-to-back-detectors-with-dashcamnetand-vehiclemakenet-not-classifying-correctly/220606
Hello,
Hardware Platform (Jetson / GPU) dGPU RTX 3080 on Ubuntu 20.04.1
DeepStream Version 6.1
TensorRT Version 8.4.1
NVIDIA GPU Driver Version (valid for GPU only) 515.48.07
I'm trying to use the back-to-back-detectors reference C application with the DashCamNet and VehicleMakeNet models. The DashCamNet detector works, but the VehicleMakeNet classifier is only outputing whatever the first entry in the labels file is (Acura in this case).
The changes I've made is from lines 89 to 103, I've replaced that all with an if statement that will print out any classifier metadata if it exists along with instantiating variables, changing the config names and changing the sink to "fake-renderer".
if (obj_meta->classifier_meta_list) {
class_meta = (NvDsClassifierMeta * )(obj_meta->classifier_meta_list->data);
if (class_meta->label_info_list) {
label_info = (NvDsLabelInfo * )(class_meta->label_info_list->data);
g_print("Result: %s\n", label_info->result_label);
}
}
DashCamNet Configuration:
[property]
gpu-id=0
net-scale-factor=0.00392156862745098
offsets=0.0;0.0;0.0
tlt-model-key=tlt_encode
tlt-encoded-model=models/tao_pretrained_models/dashcamnet/resnet18_dashcamnet_pruned.etlt
labelfile-path=models/tao_pretrained_models/dashcamnet/labels.txt
int8-calib-file=models/tao_pretrained_models/dashcamnet/dashcamnet_int8.txt
model-engine-file=models/tao_pretrained_models/dashcamnet/resnet18_dashcamnet_pruned.etlt_b1_gpu0_int8.engine
infer-dims=3;544;960
uff-input-blob-name=input_1
batch-size=1
process-mode=1
model-color-format=0
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=1
num-detected-classes=4
interval=0
gie-unique-id=1
output-blob-names=output_cov/Sigmoid;output_bbox/BiasAdd
model-color-format=0
maintain-aspect-ratio=0
output-tensor-meta=0
[class-attrs-all]
pre-cluster-threshold=0.2
group-threshold=1
## Set eps=0.7 and minBoxes for cluster-mode=1(DBSCAN)
eps=0.2
#minBoxes=3
VehicleMakeNet
[property]
batch-size=4
classifier-threshold=0.95
gie-unique-id=4
gpu-id=0
input-dims=3;224;224;0
int8-calib-file=models/VehicleMake/vehiclemakenet_int8.txt
labelfile-path=models/VehicleMake/labels_vehiclemakenet.txt
model-color-format=0
model-engine-file=models/VehicleMake/resnet18_vehiclemakenet_pruned.etlt_b4_gpu0_int8.engine
net-scale-factor=1
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=1
network-type=1
num-detected-classes=4
offsets=124;117;104
operate-on-gie-id=1
output-blob-names=predictions/Softmax
process-mode=2
tlt-encoded-model=models/VehicleMake/resnet18_vehiclemakenet_pruned.etlt
tlt-model-key=tlt_encode
uff-input-blob-name=input_1
Full code
/*
* Copyright (c) 2020-2021, NVIDIA CORPORATION. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include <gst/gst.h>
#include <glib.h>
#include <stdio.h>
#include "gstnvdsmeta.h"
#include <cuda_runtime_api.h>
#define MAX_DISPLAY_LEN 64
#define PGIE_CLASS_ID_VEHICLE 0
#define PGIE_CLASS_ID_PERSON 2
#define SGIE_CLASS_ID_LP 1
#define SGIE_CLASS_ID_FACE 0
/* Change this to 0 to make the 2nd detector act as a primary(full-frame) detector.
* When set to 1, it will act as secondary(operates on primary detected objects). */
#define SECOND_DETECTOR_IS_SECONDARY 1
/* The muxer output resolution must be set if the input streams will be of
* different resolution. The muxer will scale all the input frames to this
* resolution. */
#define MUXER_OUTPUT_WIDTH 1280
#define MUXER_OUTPUT_HEIGHT 720
/* Muxer batch formation timeout, for e.g. 40 millisec. Should ideally be set
* based on the fastest source's framerate. */
#define MUXER_BATCH_TIMEOUT_USEC 40000
gint frame_number = 0;
gchar pgie_classes_str[4][32] = { "Vehicle", "TwoWheeler", "Person",
"Roadsign"
};
#define PRIMARY_DETECTOR_UID 1
#define SECONDARY_DETECTOR_UID 2
/* nvvidconv_sink_pad_buffer_probe will extract metadata received on nvvideoconvert sink pad
* and update params for drawing rectangle, object information etc. */
static GstPadProbeReturn
nvvidconv_sink_pad_buffer_probe (GstPad * pad, GstPadProbeInfo * info,
gpointer u_data)
{
GstBuffer *buf = (GstBuffer *) info->data;
NvDsObjectMeta *obj_meta = NULL;
guint vehicle_count = 0;
guint person_count = 0;
guint face_count = 0;
guint lp_count = 0;
NvDsMetaList * l_frame = NULL;
NvDsMetaList * l_obj = NULL;
NvDsDisplayMeta *display_meta = NULL;
NvDsClassifierMeta *class_meta = NULL;
NvDsLabelInfo *label_info = NULL;
NvDsBatchMeta *batch_meta = gst_buffer_get_nvds_batch_meta (buf);
for (l_frame = batch_meta->frame_meta_list; l_frame != NULL;
l_frame = l_frame->next) {
NvDsFrameMeta *frame_meta = (NvDsFrameMeta *) (l_frame->data);
int offset = 0;
for (l_obj = frame_meta->obj_meta_list; l_obj != NULL;
l_obj = l_obj->next) {
obj_meta = (NvDsObjectMeta *) (l_obj->data);
/* Check that the object has been detected by the primary detector
* and that the class id is that of vehicles/persons. */
if (obj_meta->unique_component_id == PRIMARY_DETECTOR_UID) {
if (obj_meta->class_id == PGIE_CLASS_ID_VEHICLE)
vehicle_count++;
if (obj_meta->class_id == PGIE_CLASS_ID_PERSON)
person_count++;
}
if (obj_meta->classifier_meta_list) {
class_meta = (NvDsClassifierMeta * )(obj_meta->classifier_meta_list->data);
if (class_meta->label_info_list) {
label_info = (NvDsLabelInfo * )(class_meta->label_info_list->data);
g_print("Result: %s\n", label_info->result_label);
}
}
}
display_meta = nvds_acquire_display_meta_from_pool(batch_meta);
NvOSD_TextParams *txt_params = &display_meta->text_params[0];
display_meta->num_labels = 1;
txt_params->display_text = g_malloc0 (MAX_DISPLAY_LEN);
offset = snprintf(txt_params->display_text, MAX_DISPLAY_LEN, "Person = %d ", person_count);
offset += snprintf(txt_params->display_text + offset , MAX_DISPLAY_LEN, "Vehicle = %d ", vehicle_count);
offset += snprintf(txt_params->display_text + offset , MAX_DISPLAY_LEN, "Face = %d ", face_count);
offset += snprintf(txt_params->display_text + offset , MAX_DISPLAY_LEN, "License Plate = %d ", lp_count);
/* Now set the offsets where the string should appear */
txt_params->x_offset = 10;
txt_params->y_offset = 12;
/* Font , font-color and font-size */
txt_params->font_params.font_name = "Serif";
txt_params->font_params.font_size = 10;
txt_params->font_params.font_color.red = 1.0;
txt_params->font_params.font_color.green = 1.0;
txt_params->font_params.font_color.blue = 1.0;
txt_params->font_params.font_color.alpha = 1.0;
/* Text background color */
txt_params->set_bg_clr = 1;
txt_params->text_bg_clr.red = 0.0;
txt_params->text_bg_clr.green = 0.0;
txt_params->text_bg_clr.blue = 0.0;
txt_params->text_bg_clr.alpha = 1.0;
nvds_add_display_meta_to_frame(frame_meta, display_meta);
}
g_print ("Frame Number = %d Vehicle Count = %d Person Count = %d"
" Face Count = %d License Plate Count = %d\n",
frame_number, vehicle_count, person_count,
face_count, lp_count);
frame_number++;
return GST_PAD_PROBE_OK;
}
static gboolean
bus_call (GstBus * bus, GstMessage * msg, gpointer data)
{
GMainLoop *loop = (GMainLoop *) data;
switch (GST_MESSAGE_TYPE (msg)) {
case GST_MESSAGE_EOS:
g_print ("End of stream\n");
g_main_loop_quit (loop);
break;
case GST_MESSAGE_ERROR:{
gchar *debug;
GError *error;
gst_message_parse_error (msg, &error, &debug);
g_printerr ("ERROR from element %s: %s\n",
GST_OBJECT_NAME (msg->src), error->message);
if (debug)
g_printerr ("Error details: %s\n", debug);
g_free (debug);
g_error_free (error);
g_main_loop_quit (loop);
break;
}
default:
break;
}
return TRUE;
}
int
main (int argc, char *argv[])
{
GMainLoop *loop = NULL;
GstElement *pipeline = NULL, *source = NULL, *h264parser = NULL,
*decoder = NULL, *streammux = NULL, *sink = NULL, *primary_detector = NULL,
*secondary_detector = NULL, *nvvidconv = NULL, *nvosd = NULL;
GstElement *transform = NULL;
GstBus *bus = NULL;
guint bus_watch_id;
GstPad *nvvidconv_sink_pad = NULL;
int current_device = -1;
cudaGetDevice(&current_device);
struct cudaDeviceProp prop;
cudaGetDeviceProperties(&prop, current_device);
/* Check input arguments */
if (argc != 2) {
g_printerr ("Usage: %s <H264 filename>\n", argv[0]);
return -1;
}
/* Standard GStreamer initialization */
gst_init (&argc, &argv);
loop = g_main_loop_new (NULL, FALSE);
/* Create gstreamer elements */
/* Create Pipeline element that will form a connection of other elements */
pipeline = gst_pipeline_new ("pipeline");
/* Source element for reading from the file */
source = gst_element_factory_make ("filesrc", "file-source");
/* Since the data format in the input file is elementary h264 stream,
* we need a h264parser */
h264parser = gst_element_factory_make ("h264parse", "h264-parser");
/* Use nvdec_h264 for hardware accelerated decode on GPU */
decoder = gst_element_factory_make ("nvv4l2decoder", "nvv4l2-decoder");
/* Create nvstreammux instance to form batches from one or more sources. */
streammux = gst_element_factory_make ("nvstreammux", "stream-muxer");
if (!pipeline || !streammux) {
g_printerr ("One element could not be created. Exiting.\n");
return -1;
}
/* Create two nvinfer instances for the two back-to-back detectors */
primary_detector = gst_element_factory_make ("nvinfer", "primary-nvinference-engine1");
secondary_detector = gst_element_factory_make ("nvinfer", "primary-nvinference-engine2");
/* Use convertor to convert from NV12 to RGBA as required by nvosd */
nvvidconv = gst_element_factory_make ("nvvideoconvert", "nvvideo-converter");
/* Create OSD to draw on the converted RGBA buffer */
nvosd = gst_element_factory_make ("nvdsosd", "nv-onscreendisplay");
/* Finally render the osd output */
if(prop.integrated) {
transform = gst_element_factory_make ("nvegltransform", "nvegl-transform");
}
sink = gst_element_factory_make("fakesink", "fake-renderer");
if (!source || !h264parser || !decoder || !primary_detector || !secondary_detector
|| !nvvidconv || !nvosd || !sink) {
g_printerr ("One element could not be created. Exiting.\n");
return -1;
}
if(prop.integrated) {
if(!transform) {
g_printerr ("One tegra element could not be created. Exiting.\n");
return -1;
}
}
/* we set the input filename to the source element */
g_object_set (G_OBJECT (source), "location", argv[1], NULL);
g_object_set (G_OBJECT (streammux), "width", MUXER_OUTPUT_WIDTH, "height",
MUXER_OUTPUT_HEIGHT, "batch-size", 1,
"batched-push-timeout", MUXER_BATCH_TIMEOUT_USEC, NULL);
/* Set the config files for the two detectors. We demonstrate this by using
* the same detector model twice but making them act as vehicle-only and
* person-only detectors by adjusting the bbox confidence thresholds in the
* two seperate config files. */
g_object_set (G_OBJECT (primary_detector), "config-file-path", "dashcamnet_config.txt",
"unique-id", PRIMARY_DETECTOR_UID, NULL);
g_object_set (G_OBJECT (secondary_detector), "config-file-path", "vehicletypenet_sgie_config.txt",
"unique-id", SECONDARY_DETECTOR_UID, "process-mode", 2, NULL);
/* we add a message handler */
bus = gst_pipeline_get_bus (GST_PIPELINE (pipeline));
bus_watch_id = gst_bus_add_watch (bus, bus_call, loop);
gst_object_unref (bus);
/* Set up the pipeline */
/* we add all elements into the pipeline */
if(prop.integrated) {
gst_bin_add_many (GST_BIN (pipeline),
source, h264parser, decoder, streammux, primary_detector, secondary_detector,
nvvidconv, nvosd, transform, sink, NULL);
} else {
gst_bin_add_many (GST_BIN (pipeline),
source, h264parser, decoder, streammux, primary_detector, secondary_detector,
nvvidconv, nvosd, sink, NULL);
}
GstPad *sinkpad, *srcpad;
gchar pad_name_sink[16] = "sink_0";
gchar pad_name_src[16] = "src";
sinkpad = gst_element_get_request_pad (streammux, pad_name_sink);
if (!sinkpad) {
g_printerr ("Streammux request sink pad failed. Exiting.\n");
return -1;
}
srcpad = gst_element_get_static_pad (decoder, pad_name_src);
if (!srcpad) {
g_printerr ("Decoder request src pad failed. Exiting.\n");
return -1;
}
if (gst_pad_link (srcpad, sinkpad) != GST_PAD_LINK_OK) {
g_printerr ("Failed to link decoder to stream muxer. Exiting.\n");
return -1;
}
gst_object_unref (sinkpad);
gst_object_unref (srcpad);
/* we link the elements together */
/* file-source -> h264-parser -> nvh264-decoder ->
* nvinfer -> nvvidconv -> nvosd -> video-renderer */
if (!gst_element_link_many (source, h264parser, decoder, NULL)) {
g_printerr ("Elements could not be linked: 1. Exiting.\n");
return -1;
}
if(prop.integrated) {
if (!gst_element_link_many (streammux, primary_detector, secondary_detector,
nvvidconv, nvosd, transform, sink, NULL)) {
g_printerr ("Elements could not be linked: 2. Exiting.\n");
return -1;
}
} else {
if (!gst_element_link_many (streammux, primary_detector, secondary_detector,
nvvidconv, nvosd, sink, NULL)) {
g_printerr ("Elements could not be linked: 2. Exiting.\n");
return -1;
}
}
/* Lets add probe to get informed of the meta data generated, we add probe to
* the sink pad of the nvvideoconvert element, since by that time, the buffer would have
* had got all the metadata. */
nvvidconv_sink_pad = gst_element_get_static_pad (nvvidconv, "sink");
if (!nvvidconv_sink_pad)
g_print ("Unable to get sink pad\n");
else
gst_pad_add_probe (nvvidconv_sink_pad, GST_PAD_PROBE_TYPE_BUFFER,
nvvidconv_sink_pad_buffer_probe, NULL, NULL);
/* Set the pipeline to "playing" state */
g_print ("Now playing: %s\n", argv[1]);
gst_element_set_state (pipeline, GST_STATE_PLAYING);
/* Wait till pipeline encounters an error or EOS */
g_print ("Running...\n");
g_main_loop_run (loop);
/* Out of the main loop, clean up nicely */
g_print ("Returned, stopping playback\n");
gst_element_set_state (pipeline, GST_STATE_NULL);
g_print ("Deleting pipeline\n");
gst_object_unref (GST_OBJECT (pipeline));
g_source_remove (bus_watch_id);
g_main_loop_unref (loop);
return 0;
}

Answer 1

I think the issue was that the labels.txt file that was provided for the model needed to be comma seperated and doesn’t work if it’s seperated by new lines.