Can enable file sink only when detect object?

• Hardware Platform (Jetson / GPU)
NVIDIA Jetson Nano (Developer Kit Version)
• DeepStream Version
5.0.0
• JetPack Version (valid for Jetson only)
4.4[L4T 32.4.3]
• TensorRT Version
7.1.3.0
• NVIDIA GPU Driver Version (valid for GPU only)
I don’t know how to find GPU Driver Version on Jetson nano

I use deepstream-app.c example in /sources/apps/sample_apps/ , and I write some custom code in all_bbox_generated() function in order to record bbox infomation(x,y,w,h) in .csv file when bbox is at specific area of image.
I want to modify file sink logic to record only when detect object link person or vehicle, but I don’t know where the code that controls file sink record, is that possible?

1 Like

Do you want to save the video or just the bbox info, can you refer deepstream_app.c -> write_kitti_output

Hi, bcao
I just want to save the video which only contains detected object, because the file sink will record video without any conditions.

Pls refer smart record to see if it can meet your requirement

I use it with deepstream-test5, but it seems not working.

here is config file:

# Copyright (c) 2019 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.

[application]
enable-perf-measurement=1
perf-measurement-interval-sec=5
#gie-kitti-output-dir=streamscl

[tiled-display]
enable=1
rows=2
columns=2
width=1920
height=1080
gpu-id=0
#(0): nvbuf-mem-default - Default memory allocated, specific to particular platform
#(1): nvbuf-mem-cuda-pinned - Allocate Pinned/Host cuda memory, applicable for Tesla
#(2): nvbuf-mem-cuda-device - Allocate Device cuda memory, applicable for Tesla
#(3): nvbuf-mem-cuda-unified - Allocate Unified cuda memory, applicable for Tesla
#(4): nvbuf-mem-surface-array - Allocate Surface Array memory, applicable for Jetson
nvbuf-memory-type=0

[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtspt://admin:admin@192.168.168.228:554/media/video1
num-sources=1
rtsp-reconnect-interval-sec=1
latency=0
#select-rtp-protocol=4
#drop-frame-interval=2
gpu-id=0
# (0): memtype_device   - Memory type Device
# (1): memtype_pinned   - Memory type Host Pinned
# (2): memtype_unified  - Memory type Unified
cudadec-memtype=0
smart-record=1
smart-rec-duration=10
smart-rec-video-cache=5
smart-rec-start-time=0
smart-rec-default-duration=10
smart-rec-container=0

[source1]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtspt://admin:admin@192.168.168.224:554/media/video1
num-sources=1
rtsp-reconnect-interval-sec=1
latency=0
#select-rtp-protocol=4
#drop-frame-interval=2
gpu-id=0
# (0): memtype_device   - Memory type Device
# (1): memtype_pinned   - Memory type Host Pinned
# (2): memtype_unified  - Memory type Unified
cudadec-memtype=0
smart-record=1
smart-rec-duration=10
smart-rec-video-cache=5
smart-rec-start-time=0
smart-rec-default-duration=10
smart-rec-container=0

[source2]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtspt://admin:admin@192.168.168.225:554/media/video1
num-sources=1
rtsp-reconnect-interval-sec=1
latency=0
#select-rtp-protocol=4
#drop-frame-interval=2
gpu-id=0
# (0): memtype_device   - Memory type Device
# (1): memtype_pinned   - Memory type Host Pinned
# (2): memtype_unified  - Memory type Unified
cudadec-memtype=0
smart-record=1
smart-rec-duration=10
smart-rec-video-cache=5
smart-rec-start-time=0
smart-rec-default-duration=10
smart-rec-container=0


[source3]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP
type=4
#uri=file://../../streams/sample_1080p_h264.mp4
uri=rtspt://admin:admin@192.168.168.230:554/media/video1
num-sources=1
rtsp-reconnect-interval-sec=1
latency=0
#select-rtp-protocol=4
#drop-frame-interval=2
gpu-id=0
# (0): memtype_device   - Memory type Device
# (1): memtype_pinned   - Memory type Host Pinned
# (2): memtype_unified  - Memory type Unified
cudadec-memtype=0
smart-record=1
smart-rec-duration=10
smart-rec-video-cache=5
smart-rec-start-time=0
smart-rec-default-duration=10
smart-rec-container=0

[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=2
sync=0
source-id=0
gpu-id=0
qos=1
nvbuf-memory-type=0
overlay-id=1

[sink1]
enable=0
type=3
#1=mp4 2=mkv
container=1
#1=h264 2=h265
codec=1
sync=0
#iframeinterval=10
bitrate=4000000
output-file=out.mp4
source-id=0
#rtsp-port=8554

[sink2]
enable=0
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming
type=4
#1=h264 2=h265
codec=1
sync=0
bitrate=4000000
# set below properties in case of RTSPStreaming
rtsp-port=8554
#udp-port=5400
source-id=0

[osd]
enable=1
gpu-id=0
border-width=1
text-size=15
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Serif
show-clock=0
clock-x-offset=800
clock-y-offset=820
clock-text-size=12
clock-color=1;0;0;0
nvbuf-memory-type=0

[streammux]
gpu-id=0
##Boolean property to inform muxer that sources are live
live-source=1
batch-size=2
##time out in usec, to wait after the first buffer is available
##to push the batch even if the complete batch is not formed
batched-push-timeout=40000
## Set muxer output width and height
width=1920
height=1080
##Enable to maintain aspect ratio wrt source, and allow black borders, works
##along with width, height properties
enable-padding=0
nvbuf-memory-type=0

# config-file property is mandatory for any gie section.
# Other properties are optional and if set will override the properties set in
# the infer config file.
[primary-gie]
enable=1
gpu-id=0
labelfile-path=/opt/nvidia/deepstream/deepstream-5.0/samples/models/Primary_Detector/labels.txt
model-engine-file=/opt/nvidia/deepstream/deepstream-5.0/samples/models/Primary_Detector_Nano/resnet10.caffemodel_b8_fp16.engine
batch-size=4
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;0
bbox-border-color1=0;1;0;0
bbox-border-color2=0;1;0;1
bbox-border-color3=1;1;0;0
interval=4
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary_nano.txt

[tracker]
enable=1
tracker-width=480
tracker-height=272
#ll-lib-file=/opt/nvidia/deepstream/deepstream-4.0/lib/libnvds_mot_iou.so
ll-lib-file=/opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_klt.so
#ll-config-file required for IOU only
#ll-config-file=iou_config.txt
gpu-id=0


[tests]
file-loop=0

Can it generate video with your config?

No, it did not generate any video