DeepStream Reference Application - deepstream-app

Application Architecture

The image below shows the architecture of the NVIDIA^® DeepStream reference application.

The DeepStream reference application is a GStreamer based solution and consists of set of GStreamer plugins encapsulating low-level APIs to form a complete graph. The reference application has capability to accept input from various sources like camera, RTSP input, encoded file input, and additionally supports multi stream/source capability. The list of GStreamer plugins implemented by NVIDIA and provided as a part of DeepStream SDK include:

• The Stream Muxer plugin (Gst-nvstreammux) to form a batch of buffers from multiple input sources.

• The Preprocess plugin (Gst-nvdspreprocess) for preprocessing on the pre-defined ROIs for primary inferencing.

• The NVIDIA TensorRT™ based plugin (Gst-nvinfer) for primary and secondary (attribute classification of primary objects) detection and classification respectively.

• The Multi-Object Tracker plugin (Gst-nvtracker) for object tracking with unique ID.

• The Multi Stream Tiler plugin (Gst-nvmultistreamtiler) for forming 2D array of frames.

• The Onscreen Display (OSD) plugin (Gst-nvdsosd) to draw shaded boxes, rectangles and text on the composited frame using the generated metadata.

• The Message Converter (Gst-nvmsgconv) and Message Broker (Gst-nvmsgbroker) plugins in combination to send analytics data to a server in the Cloud.

Reference Application Configuration

The NVIDIA DeepStream SDK reference application uses one of the sample configuration files from the samples/configs/deepstream-app directory in the DeepStream package to:

• Enable or disable components

• Change the properties or behavior of components

• Customize other application configuration settings that are unrelated to the pipeline and its components

The configuration file uses a key file format, based on the freedesktop specifications at: https://specifications.freedesktop.org/desktop-entry-spec/latest

Expected Output for the DeepStream Reference Application (deepstream-app)

The image below shows the expected output with preprocess plugin disabled:

The image below shows the expected output with preprocess plugin enabled (Green bboxes are pre-defined ROIs):

Configuration Groups

The application configuration is divided into groups of configurations for each component and application-specific component. The configuration groups are:

Configuration Groups - deepstream app

Group	Configuration Group
Application Group	Application configurations that are not related to a specific component.
Tiled-display Group	Tiled display in the application.
Source Group	Source properties. There can be multiple sources. The groups must be named as: [source0], [source1] …
Source-list and source-attr-all Groups	Source URI provided as a list. There can be multiple sources. The groups must be named as: [source-list] and [source-attr-all]
Streammux Group	Specify properties and modify behavior of the streammux component.
Preprocess Group	Specify properties and modify behavior of the preprocess component.
Primary GIE and Secondary GIE Group	Specify properties and modify behavior of the primary GIE. Specify properties and modify behavior of the secondary GIE. The groups must be named as: [secondary-gie0], [secondary-gie1] …
Tracker Group	Specify properties and modify behavior of the object tracker.
Message Converter Group	Specify properties and modify behavior of the message converter component.
Message Consumer Group	Specify properties and modify behavior of message consumer components. The pipeline can contain multiple message consumer components. Groups must be named as [message-consumer0], [message-consumer1] …
OSD Group	Specify properties and modify the on-screen display (OSD) component that overlays text and rectangles on the frame.
Sink Group	Specify properties and modify behavior of sink components that represent outputs such as displays and files for rendering, encoding, and file saving. The pipeline can contain multiple sinks. Groups must be named as: [sink0], [sink1] …
Tests Group	Diagnostics and debugging. This group is experimental.
NvDs-analytics Group	Specify nvdsanalytics plugin configuration file, and to add the plugin in the application

Application Group

The application group properties are:

Application group

Key	Meaning	Type and Value	Example	Platforms
enable-perf-measurement	Indicates whether the application performance measurement is enabled.	Boolean	enable-perf-measurement=1	dGPU, Jetson
perf-measurement-interval-sec	The interval, in seconds, at which the performance metrics are sampled and printed.	Integer, >0	perf-measurement-interval-sec=10	dGPU, Jetson
gie-kitti-output-dir	Pathname of an existing directory where the application stores primary detector output in a modified KITTI metadata format.	String	gie-kitti-output-dir=­/home/­ubuntu/­kitti_data/	dGPU, Jetson
kitti-track-output-dir	Pathname of an existing directory where the application stores tracker output in a modified KITTI metadata format.	String	kitti-track-output-dir=­/home/­ubuntu/­kitti_data_tracker/	dGPU, Jetson
reid-track-output-dir	Pathname of an existing directory where the application stores tracker’s Re-ID feature output. Each line’s first integer is object id, and the remaining floats are its feature vector.	String	reid-track-output-dir=­/home/­ubuntu/­reid_data_tracker/	dGPU, Jetson
terminated-track-output-dir	Pathname of an existing directory where the application stores terminated tracker output in a modified KITTI metadata format.	String	kitti-track-output-dir=­/home/­ubuntu/­terminated_data_tracker/	dGPU, Jetson
shadow-track-output-dir	Pathname of an existing directory where the application stores shadow track state output in a modified KITTI metadata format.	String	shadow-track-output-dir=­/home/­ubuntu/­shadow_data_tracker/	dGPU, Jetson
global-gpu-id	Set Global GPU ID for all the componenents at once if needed	Integer	global-gpu-id=1	dGPU, Jetson

Tiled-display Group

The tiled-display group properties are:

Tiled display group

Key	Meaning	Type and Value	Example	Platforms
enable	Indicates whether tiled display is enabled. When user sets enable=2, first [sink] group with the key: link-to-demux=1 shall be linked to demuxer’s src_[source_id] pad where source_id is the key set in the corresponding [sink] group.	Integer, 0 = disabled, 1 = tiler-enabled 2 = tiler-and-parallel-demux-to-sink-enabled	enable=1	dGPU, Jetson
rows	Number of rows in the tiled 2D array.	Integer, >0	rows=5	dGPU, Jetson
columns	Number of columns in the tiled 2D array.	Integer, >0	columns=6	dGPU, Jetson
width	Width of the tiled 2D array, in pixels.	Integer, >0	width=1280	dGPU, Jetson
height	Height of the tiled 2D array, in pixels.	Integer, >0	height=720	dGPU, Jetson
gpu-id	GPU to be used by the element in case of multiple GPUs.	Integer, ≥0	gpu-id=0	dGPU
nvbuf-memory-type	Type of memory the element is to allocate for output buffers. 0 (nvbuf-mem-default): a platform-specific default type 1 (nvbuf-mem-cuda-pinned): pinned/host CUDA memory 2 (nvbuf-mem-cuda-device): device CUDA memory 3 (nvbuf-mem-cuda-unified): unified CUDA memory For dGPU: All values are valid. For Jetson: Only 0 (zero) is valid.	Integer, 0, 1, 2, or 3	nvbuf-memory-type=3	dGPU, Jetson
compute-hw	Compute Scaling HW to use. Applicable only for Jetson. dGPU systems uses GPU by default. 0 (Default): Default, GPU for Tesla, VIC for Jetson 1 (GPU): GPU 2 (VIC): VIC	Integer: 0-2	compute-hw=1	Jetson
square-seq-grid	Enable automatic square tiling according to number of sources. The tiles are placed sequentially on the grid with empty tiles at the end	Boolean	square-seq-grid=1	dGPU, Jetson

Source Group

The source group specifies the source properties. The DeepStream application supports multiple simultaneous sources. For each source, a separate group with the group names such as source%d must be added to the configuration file. For example:

[source0]
key1=value1
key2=value2
...

[source1]
key1=value1
key2=value2
...

The source group properties are:

Source group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the source.	Boolean	enable=1	dGPU, Jetson
type	Type of source; other properties of the source depend on this type. 1: Camera (V4L2) 2: URI 3: MultiURI 4: RTSP 5: Camera (CSI) (Jetson only)	Integer, 1, 2, 3, 4, or 5	type=1	dGPU, Jetson
uri	URI to the encoded stream. The URI can be a file, an HTTP URI, or an RTSP live source. Valid when type=2 or 3. With MultiURI, the %d format specifier can also be used to specify multiple sources. The application iterates from 0 to num-sources−1 to generate the actual URIs.	String	uri=file:///home/ubuntu/source.mp4 uri=http://127.0.0.1/source.mp4 uri=rtsp://127.0.0.1/source1 uri=file:///home/ubuntu/source_%d.mp4	dGPU, Jetson
num-sources	Number of sources. Valid only when type=3.	Integer, ≥0	num-sources=2	dGPU, Jetson
intra-decode-enable	Enables or disables intra-only decode.	Boolean	intra-decode-enable=1	dGPU, Jetson
num-extra-surfaces	Number of surfaces in addition to minimum decode surfaces given by the decoder. Can be used to manage the number of decoder output buffers in the pipeline.	Integer, ≥0 and ≤24	num-extra-surfaces=5	dGPU, Jetson
gpu-id	GPU to be used by the element in case of multiple GPUs.	Integer, ≥0	gpu-id=1	dGPU
camera-id	Unique ID for the input source to be added to metadata. (Optional)	Integer, ≥0	camera-id=2	dGPU, Jetson
camera-width	Width of frames to be requested from the camera, in pixels. Valid when type=1 or 5.	Integer, >0	camera-width=1920	dGPU, Jetson
camera-height	Height of frames to be requested from the camera, in pixels. Valid when type=1 or 5.	Integer, >0	camera-height=1080	dGPU, Jetson
camera-fps-n	Numerator part of a fraction specifying the frame rate requested by the camera, in frames/sec. Valid when type=1 or 5.	Integer, >0	camera-fps-n=30	dGPU, Jetson
camera-fps-d	Denominator part of a fraction specifying the frame rate requested from the camera, in frames/sec. Valid when type=1 or 5.	Integer, >0	camera-fps-d=1	dGPU, Jetson
camera-v4l2-dev-node	Number of the V4L2 device node. For example, /dev/video<num> for the open source V4L2 camera capture path. Valid when the type setting (type of source) is 1.	Integer, >0	camera-v4l2-dev-node=1	dGPU, Jetson
latency	Jitterbuffer size in milliseconds; applicable only for RTSP streams.	Integer, ≥0	latency=200	dGPU, Jetson
camera-csi-sensor-id	Sensor ID of the camera module. Valid when the type (type of source) is 5.	Integer, ≥0	camera-csi-sensor-id=1	Jetson
drop-frame-interval	Interval to drop frames. For example, 5 means decoder outputs every fifth frame; 0 means no frames are dropped.	Integer,	drop-frame-interval=5	dGPU, Jetson
cudadec-memtype	Type of CUDA memory element used to allocate for output buffers for source of type 2,3 or 4. Not applicable for CSI or USB camera source 0 (memtype_device): Device memory allocated with cudaMalloc(). 1 (memtype_pinned): host/pinned memory allocated with cudaMallocHost(). 2 (memtype_unified): Unified memory allocated with cudaMallocManaged().	Integer, 0, 1, or 2	cudadec-memtype=1	dGPU
nvbuf-memory-type	Type of CUDA memory the element is to allocate for output buffers of nvvideoconvert, useful for source of type 1. 0 (nvbuf-mem-default, a platform-specific default 1 (nvbuf-mem-cuda-pinned): pinned/host CUDA memory. 2 (nvbuf-mem-cuda-device): Device CUDA memory. 3 (nvbuf-mem-cuda-unified): Unified CUDA memory. For dGPU: All values are valid. For Jetson: Only 0 (zero) is valid.	Integer, 0, 1, 2, or 3	nvbuf-memory-type=3	dGPU,Jetson
select-rtp-protocol	Transport Protocol to use for RTP. Valid when type (type of source) is 4. 0: UDP + UDP Multicast + TCP 4: TCP only	Integer, 0 or 4	select-rtp-protocol=4	dGPU, Jetson
rtsp-reconnect-interval-sec	Timeout in seconds to wait since last data was received from an RTSP source before forcing a reconnection. Setting it to 0 will disable the reconnection. Valid when type (type of source) is 4.	Integer, ≥0	rtsp-reconnect-interval-sec=60	dGPU, Jetson
rtsp-reconnect-attempts	Maximum number of times a reconnection is attempted. Setting it to -1 means reconnection will be attempted infinitely. Valid when type of source is 4 and rtsp-reconnect-interval-sec is a non-zero positive value.	Integer, ≥-1	rtsp-reconnect-attempts=2
smart-record	Ways to trigger the smart record. 0: Disable 1: Only through cloud messages 2: Cloud message + Local events	Integer, 0, 1 or 2	smart-record=1	dGPU, Jetson
smart-rec-dir-path	Path of directory to save the recorded file. By default, the current directory is used.	String	smart-rec-dir-path=/home/nvidia/	dGPU, Jetson
smart-rec-file-prefix	Prefix of file name for recorded video. By default, Smart_Record is the prefix. For unique file names every source must be provided with a unique prefix.	String	smart-rec-file-prefix=Cam1	dGPU, Jetson
smart-rec-cache	Size of smart record cache in seconds.	Integer, ≥0	smart-rec-cache=20	dGPU, Jetson
smart-rec-container	Container format of recorded video. MP4 and MKV containers are supported.	Integer, 0 or 1	smart-rec-container=0	dGPU, Jetson
smart-rec-start-time	Number of seconds earlier from now to start the recording. E.g. if t0 is the current time and N is the start time in seconds that means recording will start from t0 – N. Obviously for it to work the video cache size must be greater than the N.	Integer, ≥0	smart-rec-start-time=5	dGPU, Jetson
smart-rec-default-duration	In case a Stop event is not generated. This parameter will ensure the recording is stopped after a predefined default duration.	Integer, ≥0	smart-rec-default-duration=20	dGPU, Jetson
smart-rec-duration	Duration of recording in seconds.	Integer, ≥0	smart-rec-duration=15	dGPU, Jetson
smart-rec-interval	This is the time interval in seconds for SR start / stop events generation.	Integer, ≥0	smart-rec-interval=10	dGPU, Jetson
udp-buffer-size	UDP buffer size in bytes for RTSP sources.	Integer, ≥0	udp-buffer-size=2000000	dGPU, Jetson
video-format	Output video format for the source. This value is set as the output format of the nvvideoconvert element for the source.	String: NV12, I420, P010_10LE, BGRx, RGBA	video-format=RGBA	dGPU, Jetson

Source-list and source-attr-all Groups

The source-list group allows users to provide an initial list of source URI to start streaming with. This group along with [source-attr-all] can replace the need for separate [source] groups for each stream.

Also, DeepStream support (Alpha feature) dynamic sensor provisioning via REST API. For more details on this feature, please refer to the sample configuration file and deepstream reference application run command here.

For example:

[source-list]
num-source-bins=2
list=file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h264.mp4;file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h265.mp4
sgie-batch-size=8
...
[source-attr-all]
enable=1
type=3
num-sources=1
gpu-id=0
cudadec-memtype=0
latency=100
rtsp-reconnect-interval-sec=0
...

Note: [source-list] now support REST Server with use-nvmultiurisrcbin=1

For example:

[source-list]
num-source-bins=2
list=file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h264.mp4;file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h265.mp4
use-nvmultiurisrcbin=1
#sensor-id-list vector is one to one mapped with the uri-list
#identifies each sensor by a unique ID
sensor-id-list=UniqueSensorId1;UniqueSensorId2
#Optional sensor-name-list vector is one to one mapped with the uri-list
sensor-name-list=UniqueSensorName1;UniqueSensorName2
max-batch-size=10
http-ip=localhost
http-port=9000
#sgie batch size is number of sources * fair fraction of number of objects detected per frame per source
#the fair fraction of number of object detected is assumed to be 4
sgie-batch-size=40

[source-attr-all]
enable=1
type=3
num-sources=1
gpu-id=0
cudadec-memtype=0
latency=100
rtsp-reconnect-interval-sec=0

The [source-list] group properties are:

Source List group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the source.	Boolean	enable=1	dGPU, Jetson
num-source-bins	The total number of source URI’s provided with the key list	Integer	num-source-bins=2	dGPU, Jetson
sgie-batch-size	sgie batch size is number of sources * fair fraction of number of objects detected per frame per source the fair fraction of number of object detected is assumed to be 4	Integer	sgie-batch-size=8	dGPU, Jetson
list	The list of URI’s separated by semi-colon ‘;’	String	list=rtsp://ip-address:port/stream1;rtsp://ip-address:port/stream2	dGPU, Jetson
sensor-id-list	(Alpha Feature) Applicable only when use-nvmultiurisrcbin=1. The list of unique Identifiers identifying each stream separated by semi-colon ‘;’	String	sensor-id-list=UniqueSensorId1;UniqueSensorId2	dGPU
sensor-name-list	(Alpha Feature) Applicable only when use-nvmultiurisrcbin=1. The Optional list of sensor names identifying each stream separated by semi-colon ‘;’	String	sensor-name-list=SensorName1;SensorName2	dGPU
use-nvmultiurisrcbin	(Alpha Feature) Boolean if set enable the use of nvmultiurisrcbin with REST API support for dynamic sensor provisioning	Boolean	use-nvmultiurisrcbin=0(default)	dGPU
max-batch-size	(Alpha Feature) Applicable only when use-nvmultiurisrcbin=1. Sets the maximum number of sensors that can be streamed using this instance of DeepStream	Integer	max-batch-size=10	dGPU
http-ip	(Alpha Feature) Applicable only when use-nvmultiurisrcbin=1. The HTTP Endpoint IP address to use	String	http-ip=localhost (default)	dGPU
http-port	(Alpha Feature) Applicable only when use-nvmultiurisrcbin=1. The HTTP Endpoint port number to use. Note: User may pass empty string to disable REST API server	String	http-ip=9001 (default)	dGPU

The [source-attr-all] group support all properties except uri from the Source Group. A sample config file can be found at /opt/nvidia/deepstream/deepstream/sources/apps/sample_apps/deepstream-test5/configs/test5_config_file_nvmultiurisrcbin_src_list_attr_all.txt.

Streammux Group

The [streammux] group specifies and modifies properties of the Gst-nvstreammux plugin.

Streammux group

Key	Meaning	Type and Value	Example	Platforms
gpu-id	GPU element is to use in case of multiple GPUs.	Integer, ≥0	gpu-id=1	dGPU
live-source	Informs the muxer that sources are live.	Boolean	live-source=0	dGPU, Jetson
buffer-pool-size	Number of buffers in Muxer output buffer pool.	Integer, >0	buffer-pool-size=4	dGPU, Jetson
batch-size	Muxer batch size.	Integer, >0	batch-size=4	dGPU, Jetson
batched-push-timeout	Timeout in microseconds after to push the batch after the first buffer is available, even if the complete batch is not formed.	Integer, ≥−1	batched-push-timeout=40000	dGPU, Jetson
width	Muxer output width in pixels.	Integer, >0	width=1280	dGPU, Jetson
height	Muxer output height in pixels.	Integer, >0	height=720	dGPU, Jetson
enable-padding	Indicates whether to maintain source aspect ratio when scaling by adding black bands.	Boolean	enable-padding=0	dGPU, Jetson
nvbuf-memory-type	Type of CUDA memory the element is to allocate for output buffers. 0 (nvbuf-mem-default, a platform-specific default 1 (nvbuf-mem-cuda-pinned): pinned/host CUDA memory. 2 (nvbuf-mem-cuda-device): Device CUDA memory. 3 (nvbuf-mem-cuda-unified): Unified CUDA memory. For dGPU: All values are valid. For Jetson: Only 0 (zero) is valid.	Integer, 0, 1, 2, or 3	nvbuf-memory-type=3	dGPU
attach-sys-ts-as-ntp	For live sources, the muxed buffer shall have associated NvDsFrameMeta->ntp_timestamp set to system time or the server’s NTP time when streaming RTSP. If set to 1, system timestamp will be attached as ntp timestamp. If set to 0, ntp timestamp from rtspsrc, if available, will be attached.	Boolean	attach-sys-ts-as-ntp=0	dGPU, Jetson
config-file-path	This key is valid only for the new streammux. Please refer the plugin manual section “New Gst-nvstreammux” for more information. Absolute or relative (to DS config-file location) path of mux configuration file.	String	config-file-path=config_mux_source30.txt	dGPU, Jetson
sync-inputs	Time synchronize input frames before batching them.	Boolean	sync-inputs=0 (default)	dGPU, Jetson
max-latency	Additional latency in live mode to allow upstream to take longer to produce buffers for the current position (in nanoseconds).	Integer, ≥0	max-latency=0 (default)	dGPU, Jetson
drop-pipeline-eos	Boolean property to control EOS propagation downstream from nvstreammux when all the sink pads are at EOS. (Experimental)	Boolean	drop-pipeline-eos=0(default)	dGPU/Jetson

Preprocess Group

The [pre-process] group is for adding nvdspreprocess plugin in the pipeline. Supports preprocessing for only Primary GIE.

Preprocess group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the plugin.	Boolean	enable=1	dGPU, Jetson
config-file	Configuration file path for nvdspreprocess plugin	String	config-file=config_preprocess.txt	dGPU, Jetson

Primary GIE and Secondary GIE Group

The DeepStream application supports multiple secondary GIEs. For each secondary GIE, a separate group with the name secondary-gie%d must be added to the configuration file. For example:

[primary-gie]
key1=value1
key2=value2
...

[secondary-gie1]
key1=value1
key2=value2
...

The primary and secondary GIE configurations are as follows. For each configuration, the Valid for column indicates whether the configuration property is valid for the primary or secondary TensorRT model, or for both models.

Primary and Secondary GIE* group

Key	Meaning	Type and Value	Example	Platforms/ GIEs*
enable	Indicates whether the primary GIE must be enabled.	Boolean	enable=1	dGPU, Jetson Both GIEs
gie-unique-id	Unique component ID to be assigned to the nvinfer instance. Used to identify metadata generated by the instance.	Integer, >0	gie-unique-id=2	Both
gpu-id	GPU to be used by the element in case of multiple GPUs.	Integer, ≥0	gpu-id=1	dGPU, Both GIEs
model-engine-file	Absolute pathname of the pre-generated serialized engine file for the mode.	String	model-engine-file=­../../models/­Primary_Detector/­resnet18_trafficcamnet_pruned.onnx_b4_gpu0_int8.engine	Both GIEs
nvbuf-memory-type	Type of CUDA memory element is to allocate for output buffers. 0 (nvbuf-mem-default): a platform-specific default 1 (nvbuf-mem-cuda-pinned): pinned/host CUDA memory 2 (nvbuf-mem-cuda-device): Device CUDA memory 3 (nvbuf-mem-cuda-unified): Unified CUDA memory For dGPU: All values are valid. For Jetson: Only 0 (zero) is valid.	Integer, 0, 1, 2, or 3	nvbuf-memory-type=3	dGPU, Jetson Primary GIE
config-file	Pathname of a configuration file which specifies properties for the Gst-nvinfer plugin. It may contain any of the properties described in this table except config-file itself. Properties must be defined in a group named [property]. For more details about parameters see “Gst-nvinfer File Configuration Specifications” in the DeepStream 4.0 Plugin Manual.	String	config-file=¬/home/-ubuntu/-config_infer_resnet.txt For complete examples, see the sample file samples/¬configs/-deepstream-app/-config_infer_resnet.txt or the deepstream-test2 sample application.	dGPU, Jetson Both GIEs
batch-size	The number of frames(P.GIE)/objects(S.GIE) to be inferred together in a batch.	Integer, >0 Integer, >0	batch-size=2	dGPU, Jetson Both GIEs
interval	Number of consecutive batches to skip for inference.	Integer, >0 Integer, >0	interval=2	dGPU, Jetson Primary GIE
bbox-border-color	The color of the borders for the objects of a specific class ID, specified in RGBA format. The key must be of format bbox-border-color<class-id>. This property can be identified multiple times for multiple class IDs. If this property is not identified for the class ID, the borders are not drawn for objects of that class-id.	R:G:B:A Float, 0≤R,G,B,A≤1	bbox-border-color2= 1;0;0;1 (Red for class-id 2)	dGPU, Jetson Both GIEs
bbox-bg-color	The color of the boxes drawn over objects of a specific class ID, in RGBA format. The key must be of format bbox-bg-color<class-id>. This property can be used multiple times for multiple class IDs. If it is not used for a class ID, the boxes are not drawn for objects of that class ID.	R:G:B:A Float, 0≤R,G,B,A≤1	bbox-bg-color3=-0;1;0;0.3 (Semi-transparent green for class-id 3)	dGPU, Jetson Both GIEs
operate-on-gie-id	A unique ID of the GIE, on whose metadata (NvDsFrameMeta) this GIE is to operate.	Integer, >0	operate-on-gie-id=1	dGPU, Jetson Secondary GIE
operate-on-class-ids	Class IDs of the parent GIE on which this GIE must operate. The parent GIE is specified using operate-on-gie-id.	Semicolon separated integer array	operate-on-class-ids=1;2 (operate on objects with class IDs 1, 2 generated by parent GIE)	dGPU, Jetson Secondary GIE
infer-raw-output-dir	Pathname of an existing directory in which to dump the raw inference buffer contents in a file.	String	infer-raw-output-dir=­/home/­ubuntu/­infer_raw_out	dGPU, Jetson Both GIEs
labelfile-path	Pathname of the labelfile.	String	labelfile-path=../../models/Primary_Detector/labels.txt	dGPU, Jetson Both GIEs
plugin-type	Plugin to use for inference. 0: nvinfer (TensorRT) 1: nvinferserver (Triton inference server)	Integer, 0 or 1	plugin-type=1	dGPU, Jetson Both GIEs
input-tensor-meta	Use preprocessed input tensors attached as metadata by nvdspreprocess plugin instead of preprocessing inside the nvinfer.	Integer, 0 or 1	input-tensor-meta=1	dGPU, Jetson, Primary GIE

Note

* The GIEs are the GPU Inference Engines.

Tracker Group

The tracker group properties include the following, and more details can be found in Gst Properties:

Tracker group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the tracker.	Boolean	enable=1	dGPU, Jetson
tracker-width	Frame width at which the tracker will operate, in pixels. (To be a multiple of 32 when tracker config visualTrackerType: 1 or reidType is non-zero with useVPICropScaler: 0)	Integer, ≥0	tracker-width=960	dGPU, Jetson
tracker-height	Frame height at which the tracker will operate, in pixels. (To be a multiple of 32 when tracker config visualTrackerType: 1 or reidType is non-zero with useVPICropScaler: 0)	Integer, ≥0	tracker-height=544	dGPU, Jetson
gpu-id	GPU to be used by the element in case of multiple GPUs.	Integer, ≥0	gpu-id=1	dGPU
ll-config-file	Configuration file for the low-level library if needed. (Alpha feature) A list of configuration files can be specified when the property sub-batches is configured.	String	ll-config-file=iou_config.txt	dGPU, Jetson
ll-lib-file	Pathname for the low-level tracker implementation library.	String	ll-lib-file=/usr/-local/deepstream/libnvds_mot_iou.so	dGPU, Jetson
tracking-surface-type	Set surface stream type for tracking. (default value is 0)	Integer, ≥0	tracking-surface-type=0	dGPU, Jetson
display-tracking-id	Enables tracking id display.	Boolean	display-tracking-id=1	dGPU, Jetson
tracking-id-reset-mode	Allow force-reset of tracking ID based on pipeline event. Once tracking ID reset is enabled and such event happens, the lower 32-bit of the tracking ID will be reset to 0 0: Not reset tracking ID when stream reset or EOS event happens 1: Terminate all existing trackers and assign new IDs for a stream when the stream reset happens (i.e., GST_NVEVENT_STREAM_RESET) 2: Let tracking ID start from 0 after receiving EOS event (i.e., GST_NVEVENT_STREAM_EOS) (Note: Only the lower 32-bit of tracking ID to start from 0) 3: Enable both option 1 and 2	Integer, 0 to 3	tracking-id-reset-mode=0	dGPU, Jetson
input-tensor-meta	Use the tensor-meta from Gst-nvdspreprocess if available for tensor-meta-gie-id	Boolean	input-tensor-meta=1	dGPU, Jetson
tensor-meta-gie-id	Tensor Meta GIE ID to be used, property valid only if input-tensor-meta is TRUE	Unsigned Integer, ≥0	tensor-meta-gie-id=5	dGPU, Jetson
sub-batches (Alpha feature)	Configures splitting of a batch of frames in sub-batches	Semicolon delimited integer array. Must include all values from 0 to (batch-size -1) where batch-size is configured in [streammux].	sub-batches=0,1;2,3 In this example, a batch size of 4 is split into two sub-batches where the first sub-batch consists of source ids 0 & 1 and second sub-batch consists of source ids 2 & 3	dGPU, Jetson
sub-batch-err-recovery-trial-cnt (Alpha feature)	Configure the number of times the plugin can try to recover when the low level tracker in a sub-batch returns with a fatal error. To recover from the error, the plugin reinitializes the low level tracker library.	Integer,≥-1 where, -1 corresponds to infinite trials	sub-batch-err-recovery-trial-cnt=3	dGPU, Jetson
user-meta-pool-size	The size of tracker miscellaneous data buffer pool	Unsigned Integer, >0	user-meta-pool-size=32	dGPU, Jetson

Message Converter Group

Message converter group properties are:

Message converter group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the message converter.	Boolean	enable=1	dGPU, Jetson
msg-conv-config	Pathname of the configuration file for the Gst-nvmsgconv element.	String	msg-conv-config=dstest5_msgconv_sample_config.txt	dGPU, Jetson
msg-conv-payload-type	Type of payload. 0, PAYLOAD_DEEPSTREAM: Deepstream schema payload. 1, PAYLOAD_DEEPSTREAM_MINIMAL: Deepstream schema payload minimal. 256, PAYLOAD_RESERVED: Reserved type. 257, PAYLOAD_CUSTOM: Custom schema payload.	Integer 0, 1, 256, or 257	msg-conv-payload-type=0	dGPU, Jetson
msg-conv-msg2p-lib	Absolute pathname of an optional custom payload generation library. This library implements the API defined by sources/libs/nvmsgconv/nvmsgconv.h.	String	msg-conv-msg2p-lib=/opt/nvidia/deepstream/deepstream-4.0/lib/libnvds_msgconv.so	dGPU, Jetson
msg-conv-comp-id	comp-id Gst property of the gst-nvmsgconv element. This is the Id of the component that attaches the NvDsEventMsgMeta which must be processed by gst-nvmsgconv element.	Integer, >=0	msg-conv-comp-id=1	dGPU, Jetson
debug-payload-dir	Directory to dump payload	String	debug-payload-dir=<absolute path> Default is NULL	dGPU Jetson
multiple-payloads	Generate multiple message payloads	Boolean	multiple-payloads=1 Default is 0	dGPU Jetson
msg-conv-msg2p-newapi	Generate payloads using Gst buffer frame/object metadata	Boolean	msg-conv-msg2p-newapi=1 Default is 0	dGPU Jetson
msg-conv-frame-interval	Frame interval at which payload is generated	Integer, 1 to 4,294,967,295	msg-conv-frame-interval=25 Default is 30	dGPU Jetson
msg-conv-dummy-payload	By default payload is generated if NVDS_EVENT_MSG_META is attached to buffer. With this dummy payload can be generated if there is no NVDS_EVENT_MSG_META attached to buffer	boolean	msg-conv-dummy-payload=true Default is false	dGPU Jetson

Message Consumer Group

Message consumer group properties are:

Message consumer group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the message consumer.	Boolean	enable=1	dGPU, Jetson
proto-lib	Path to the library having protocol adapter implementation.	String	proto-lib=/opt/nvidia/deepstream/deepstream-4.0/lib/libnvds_kafka_proto.so	dGPU, Jetson
conn-str	Connection string of the server.	String	conn-str=foo.bar.com;80	dGPU, Jetson
config-file	Path to the file having additional configurations for protocol adapter,	String	config-file=../cfg_kafka.txt	dGPU, Jetson
subscribe-topic-list	List of topics to subscribe.	String	subscribe-topic-list=toipc1;topic2;topic3	dGPU, Jetson
sensor-list-file	File having mappings from sensor index to sensor name.	String	sensor-list-file=dstest5_msgconv_sample_config.txt	dGPU, Jetson

OSD Group

The OSD group specifies the properties and modifies the behavior of the OSD component, which overlays text and rectangles on the video frame.

OSD group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the On-Screen Display (OSD).	Boolean	enable=1	dGPU, Jetson
gpu-id	GPU to be used by the element in case of multiple GPUs.	Integer, ≥0	gpu-id=1	dGPU
border-width	Border width of the bounding boxes drawn for objects, in pixels.	Integer, ≥0	border-width=10	dGPU, Jetson
border-color	Border color of the bounding boxes drawn for objects.	R;G;B;A Float, 0≤R,G,B,A≤1	border-color=0;0;0.7;1 #Dark Blue	dGPU, Jetson
text-size	Size of the text that describes the objects, in points.	Integer, ≥0	text-size=16	dGPU, Jetson
text-color	The color of the text that describes the objects, in RGBA format.	R;G;B;A Float, 0≤R,G,B,A≤1	text-color=0;0;0.7;1 #Dark Blue	dGPU, Jetson
text-bg-color	The background color of the text that describes the objects, in RGBA format.	R;G;B;A Float, 0≤R,G,B,A≤1	text-bg-color=0;0;0;0.5 #Semi-transparent black	dGPU, Jetson
clock-text-size	The size of the clock time text, in points.	Integer, >0	clock-text-size=16	dGPU, Jetson
clock-x-offset	The horizontal offset of the clock time text, in pixels.	Integer, >0	clock-x-offset=100	dGPU, Jetson
clock-y-offset	The vertical offset of the clock time text, in pixels.	Integer, >0	clock-y-offset=100	dGPU, Jetson
font	Name of the font for text that describes the objects.	String	font=Purisa	dGPU, Jetson
	Enter the shell command fc-list to display the names of available fonts.
clock-color	Color of the clock time text, in RGBA format.	R;G;B;A Float, 0≤R,G,B,A≤1	clock-color=1;0;0;1 #Red	dGPU, Jetson
nvbuf-memory-type	Type of CUDA memory the element is to allocate for output buffers. 0 (nvbuf-mem-default): a platform-specific default 1 (nvbuf-mem-cuda-pinned): pinned/host CUDA memory 2 (nvbuf-mem-cuda-device): Device CUDA memory 3 (nvbuf-mem-cuda-unified): Unified CUDA memory For dGPU: All values are valid. For Jetson: Only 0 (zero) is valid.	Integer, 0, 1, 2, or 3	nvbuf-memory-type=3	dGPU
process-mode	NvOSD processing mode. 0: CPU 1: GPU	Integer, 0, 1, or 2	process-mode=1	dGPU, Jetson
display-text	Indicate whether to display text	Boolean	display-text=1	dGPU, Jetson
display-bbox	Indicate whether to bounding box	Boolean	display-bbox=1	dGPU, Jetson
display-mask	Indicate whether to display instance mask	Boolean	display-mask=1	dGPU, Jetson

Sink Group

The sink group specifies the properties and modifies the behavior of the sink components for rendering, encoding, and file saving.

Sink group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the sink.	Boolean	enable=1	dGPU, Jetson
type	Type of sink, to use. 1: Fakesink 2: EGL based windowed nveglglessink for dGPU and nv3dsink for Jetson 3: Encode + File Save (encoder + muxer + filesink) 4: Encode + RTSP streaming; Note: sync=1 for this type is not applicable; 5: nvdrmvideosink (Jetson only) 6: Message converter + Message broker	Integer, 1, 2, 3, 4, 5 or 6	type=2	dGPU, Jetson
sync	Indicates how fast the stream is to be rendered. 0: As fast as possible 1: Synchronously	Integer, 0 or 1	sync=1	dGPU, Jetson
qos	Indicates whether the sink is to generate Quality-of-Service events, which can lead to the pipeline dropping frames when pipeline FPS cannot keep up with the stream frame rate.	Boolean	qos=0	dGPU, Jetson
source-id	The ID of the source whose buffers this sink must use. The source ID is contained in the source group name. For example, for group [source1] source-id=1.	Integer, ≥0	source-id=1	dGPU, Jetson
gpu-id	GPU to be used by the element in case of multiple GPUs.	Integer, ≥0	gpu-id=1	dGPU
container	Container to use for the file save. Only valid for type=3. 1: MP4 2: MKV	Integer, 1 or 2	container=1	dGPU, Jetson
codec	The encoder to be used to save the file. 1: H.264 (hardware) 2: H.265 (hardware)	Integer, 1 or 2	codec=1	dGPU, Jetson
bitrate	Bitrate to use for encoding, in bits per second. Valid for type=3 and 4.	Integer, >0	bitrate=4000000	dGPU, Jetson
iframeinterval	Encoding intra-frame occurrence frequency.	Integer, 0≤iv≤MAX_INT	iframeinterval=30	dGPU, Jetson
output-file	Pathname of the output encoded file. Only valid for type=3.	String	output-file=­/home/­ubuntu/­output.mp4	dGPU, Jetson
nvbuf-memory-type	Type of CUDA memory the plugin is to allocate for output buffers. 0 (nvbuf-mem-default): a platform-specific default 1 (nvbuf-mem-cuda-pinned): pinned/host CUDA memory 2 (nvbuf-mem-cuda-device): Device CUDA memory 3 (nvbuf-mem-cuda-unified): Unified CUDA memory For dGPU: All values are valid. For Jetson: Only 0 (zero) Is valid.	Integer, 0, 1, 2, or 3	nvbuf-memory-type=3	dGPU, Jetson
rtsp-port	Port for the RTSP streaming server; a valid unused port number. Valid for type=4.	Integer	rtsp-port=8554	dGPU, Jetson
udp-port	Port used internally by the streaming implementation - a valid unused port number. Valid for type=4.	Integer	udp-port=5400	dGPU, Jetson
conn-id	Connection index. Valid for nvdrmvideosink(type=5).	Integer, >=1	conn-id=0	Jetson
width	Width of the renderer in pixels.	Integer, >=1	width=1920	dGPU, Jetson
height	Height of the renderer in pixels.	Integer, >=1	height=1920	dGPU, Jetson
offset-x	Horizontal offset of the renderer window, in pixels.	Integer, >=1	offset-x=100	dGPU, Jetson
offset-y	Vertical offset of the renderer window, in pixels.	Integer, >=1	offset-y=100	dGPU, Jetson
plane-id	Plane on which video should be rendered. Valid for nvdrmvideosink(type=5).	Integer, ≥0	plane-id=0	Jetson
msg-conv-config	Pathname of the configuration file for the Gst-nvmsgconv element (type=6).	String	msg-conv-config=dstest5_msgconv_sample_config.txt	dGPU, Jetson
msg-broker-proto-lib	Path to the protocol adapter implementation used Gst-nvmsgbroker (type=6).	String	msg-broker-proto-lib= /opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_amqp_proto.so	dGPU, Jetson
msg-broker-conn-str	Connection string of the backend server (type=6).	String	msg-broker-conn-str=foo.bar.com;80;dsapp	dGPU, Jetson
topic	Name of the message topic (type=6).	String	topic=test-ds4	dGPU, Jetson
msg-conv-payload-type	Type of payload. 0, PAYLOAD_DEEPSTREAM: DeepStream schema payload. 1, PAYLOAD_DEEPSTREAM_-MINIMAL: DeepStream schema payload minimal. 256, PAYLOAD_RESERVED: Reserved type. 257, PAYLOAD_CUSTOM: Custom schema payload (type=6).	Integer 0, 1, 256, or 257	msg-conv-payload-type=0	dGPU, Jetson
msg-broker-config	Pathname of an optional configuration file for the Gst-nvmsgbroker element (type=6).	String	msg-broker-config=/home/ubuntu/cfg_amqp.txt	dGPU, Jetson
sleep-time	Sleep time between consecutive do_work calls in milliseconds	Integer >= 0. For Azure, use value >= 10 depending on IoT Hub service tier message rate limit. Warning: failure is likely with unreasonably high sleep times, e.g. 10000000 ms	sleep-time=10	dGPU Jetson
new-api	use protocol adapter library api’s directly or use new msgbroker library wrapper api’s (type=6)	Integer 0 : Use adapter api’s directly 1 : msgbroker lib wrapper api’s	new-api = 0	dGPU, Jetson
msg-conv-msg2p-lib	Absolute pathname of an optional custom payload generation library. This library implements the API defined by sources/libs/nvmsgconv/­nvmsgconv.h. Applicable only when msg-conv-payload-type=257, PAYLOAD_CUSTOM. (type=6)	String	msg-conv-msg2p-lib= /opt/nvidia/deepstream/deepstream-4.0/lib/libnvds_msgconv.so	dGPU, Jetson
msg-conv-comp-id	comp-id Gst property of the nvmsgconv element; ID (gie-unique-id) of the primary/secondary-gie component from which metadata is to be processed. (type=6)	Integer, >=0	msg-conv-comp-id=1	dGPU, Jetson
msg-broker-comp-id	comp-id Gst property of the nvmsgbroker element; ID (gie-unique-id) of the primary/secondary gie component from which metadata is to be processed. (type=6)	Integer, >=0	msg-broker-comp-id=1	dGPU, Jetson
debug-payload-dir	Directory to dump payload (type=6)	String	debug-payload-dir=<absolute path> Default is NULL	dGPU Jetson
multiple-payloads	Generate multiple message payloads (type=6)	Boolean	multiple-payloads=1 Default is 0	“dGPU Jetson”
msg-conv-msg2p-newapi	Generate payloads using Gst buffer frame/object metadata (type=6)	Boolean	msg-conv-msg2p-newapi=1 Default is 0	“dGPU Jetson”
msg-conv-frame-interval	Frame interval at which payload is generated (type=6)	Integer, 1 to 4,294,967,295	msg-conv-frame-interval=25 Default is 30	dGPU Jetson
disable-msgconv	Only add a message broker component instead of a message converter + message broker. (type=6)	Integer,	disable-msgconv = 1	dGPU, Jetson
enc-type	Engine to use for encoder 0: NVENC hardware engine 1: CPU software encoder	Integer, 0 or 1	enc-type=0	dGPU, Jetson
profile (HW)	Encoder profile for the codec V4L2 H264 encoder(HW): 0: Baseline 2: Main 4: High V4L2 H265 encoder(HW): 0: Main 1: Main10	Integer, valid values from the column beside	profile=2	dGPU, Jetson
udp-buffer-size	UDP kernel buffer size (in bytes) for internal RTSP output pipeline.	Integer, >=0	udp-buffer-size=100000	dGPU, Jetson
link-to-demux	A boolean which enables or disables streaming a particular “source-id” alone to this sink. Please check the tiled-display group enable key for more information.	Boolean	link-to-demux=0	dGPU, Jetson

Tests Group

The tests group is for diagnostics and debugging.

Tests group

Key	Meaning	Type and Value	Example	Platforms
file-loop	Indicates whether input files should be looped infinitely.	Boolean	file-loop=1	dGPU, Jetson

NvDs-analytics Group

The [nvds-analytics] group is for adding nvds-analytics plugin in the pipeline.

NvDs-analytics group

Key	Meaning	Type and Value	Example	Platforms
enable	Enables or disables the plugin.	Boolean	enable=1	dGPU, Jetson
config-file	Configuration file path for nvdsanalytics plugin	String	config-file=config_nvdsanalytics.txt	dGPU, Jetson

Note

See the DeepStream Plugin Guide for plugin-specific configuration file specifications (for the Gst-nvdspreprocess, Gst-nvinfer, Gst-nvtracker, Gst-nvdewarper, Gst-nvmsgconv, Gst-nvmsgbroker and Gst-nvdsanalytics plugins).

Application Tuning for DeepStream SDK

This section provides application tuning tips for the DeepStream SDK using the following parameters in the configuration file.

Performance Optimization

This section covers various performance optimization steps that you can try for maximum performance.

DeepStream best practices

Here are few best practices to optimize DeepStream application to remove bottlenecks in your application:

1. Set the batch size of streammux and primary detector to equal the number of input sources. These settings are under [streammux] and [primary-gie] group of the config file. This keeps the pipeline running at full capacity. Higher or lower batch size than number of input sources can sometimes add latency in the pipeline.

2. Set the height and width of streammux to the input resolution. This is set under [streammux] group of the config file. This ensures that stream doesn’t go through any unwanted image scaling.

3. If you are streaming from live sources such as RTSP or from USB camera, set live-source=1 in [streammux] group of config file. This enables proper timestamping for live sources creating smoother playback

4. Tiling and visual output can take up GPU resource. There are 3 things that you can disable to maximize throughput when you do not need to render the output on your screen. As an example, rendering is not required when you want to run inference on the edge and transmit just the metadata to the cloud for further processing.

1. Disable OSD or on-screen display. OSD plugin is used for drawing bounding boxes and other artifacts and adding labels in the output frame. To disable OSD set enable=0 in the [osd] group of the config file.

2. The tiler creates an NxM grid for displaying the output streams. To disable the tiled output, set enable=0 in the [tiled-display] group of the config file.

3. Disable the output sink for rendering: choose fakesink, that is, type=1 in the [sink] group of the config file. All the performance benchmark in Performance section are ran with tiling, OSD and output sink disabled.

5. If CPU/GPU utilization is low, then one of the possibilities is that the elements in the pipeline are getting starved for buffers. Then try increasing the number of buffers allocated by the decoder by setting the num-extra-surfaces property of the [source#] group in the application or the num-extra-surfaces property of Gst-nvv4l2decoder element.

6. If you are running the application inside docker console and it delivers low FPS, set qos=0 in the configuration file’s [sink0] group. The issue is caused by initial load. When qos set to 1, as the property’s default value in the [sink0] group, decodebin starts dropping frames.

7. If you want to optimize processing pipelines end to end latency you can use latency measurement method in DeepStream.

• To enable frame latency measurement, run this command on the console:

  $ export NVDS_ENABLE_LATENCY_MEASUREMENT=1
  

• To enable latency for all plugins, run this command on the console:

  $ export NVDS_ENABLE_COMPONENT_LATENCY_MEASUREMENT=1
  

Note

When measuring frame latency using DeepStream latency APIs if large frame latency numbers in the order of 10^12 or 1e12 are observed, modify the latency measurement code (call to nvds_measure_buffer_latency API) to

...
guint num_sources_in_batch = nvds_measure_buffer_latency(buf, latency_info);

if (num_sources_in_batch > 0 && latency_info[0].latency > 1e6) {
  NvDsBatchMeta *batch_meta = gst_buffer_get_nvds_batch_meta (buf);
  batch_meta->batch_user_meta_list = g_list_reverse (batch_meta->batch_user_meta_list);
  num_sources_in_batch = nvds_measure_buffer_latency(buf, latency_info);
}
...

Jetson optimization

1. Ensure that Jetson clocks are set high. Run these commands to set Jetson clocks high.

   $ sudo nvpmodel -m <mode> --for MAX perf and power mode is 0
   $ sudo jetson_clocks
   

Note

For NX: use mode as 2.

2. On Jetson, use Gst-nvdrmvideosink instead of Gst-nv3dsink as nv3dsink requires GPU utilization.

Triton

1. If you are using Triton with DeepStream, tune tf_gpu_memory_fraction values for TensorFlow GPU memory usage per process - suggested range [0.2, 0.6]. Too large value can cause Out-of-memory and too small may cause low perf.

2. Enable TensorRT optimization when using TensorFlow or ONNX with Triton. Update Triton config file to enable TensorFlow/ONNX TensorRT online optimization. This will take several minutes during initialization each time. Alternatively, you can generate TF-TRT graphdef/savedmodel models offline.

Inference Throughput

Here are a few steps to help you increase channel density for your application:

1. If you are using Jetson AGX Orin or Jetson Orin NX, you can use the DLA (Deep learning accelerator) for inferencing. This frees GPU for other models or more streams.

2. With DeepStream, users can infer every other frame or every third frame and use a tracker to predict the location in the object. This can be done with a simple config file change. Users can use one of the 3 available trackers to track the object in the frame. In the inference config file, change the interval parameter under [property]. This is a skip interval, number of frames to skip between inference. Interval of 0 means infer every frames and interval of 1 means skip 1 frame and infer every other frame. This can effectively double your overall channel throughput by going from interval of 0 to 1.

3. Choose lower precision such as FP16 or INT8 for inference. If you want to use FP16, no new model is required. This is a simple change in the DS. To change, update the network-mode option in the inference config file. If you want to run INT8, an INT8 calibration cache is required which contains the FP32 to INT8 quantization table.

4. DeepStream app can also be configured to have cascaded neural network. First network does the detection followed by second network with does some classification on the detection. To enable secondary inference, enable the secondary-gie from the config file. Set the appropriate batch sizes. Batch size will depend on number of objects that are typically sent to the secondary inference from primary inference. You’ll have to experiment to see what the appropriate batch size for their use case is. To reduce the number of inferences of the secondary classifier, the objects to infer on can be filtered by setting input-object-min-width, input-object-min-height, input-object-max-width, input-object-max-height, operate-on-gie-id, operate-on-class-ids appropriately.

Reducing Spurious Detections

Reducing spurious detections

Configuration Parameter	Description	Use Case
threshold	Per-class-threshold of primary detector. Increasing the threshold restricts output to objects with higher detection confidence.	—
roi-top-offset roi-bottom-offset	Per-class top/bottom region of interest (roi) offset. Restricts output to objects in a specified region of the frame.	To reduce spurious detections seen on the dashboard of dashcams
detected-min-w detected-min-h detected-max-w detected-max-h	Per-class min/max object width/height for primary-detector Restricts output to objects of specified size.	To reduce false detections, for example, a tree being detected as a person