Please provide complete information as applicable to your setup.
• Hardware Platform: Jetson orin nano developer kit
• DeepStream Version: 6.3
• JetPack Version 5.1.3 L4T R35.6.0
• TensorRT Version: 8.5.2
ISSUE: I am using jetson orin nano on headless mode. I want to save images. So I compiled sample apps named deepstream-transfer-learning-app using sudo make and make install. And I am trying to run outputted deepstream-transfer-learning-app with yolo model. It is giving this error:
Opening in BLOCKING MODE
NvMMLiteOpen : Block : BlockType = 261
NvMMLiteBlockCreate : Block : BlockType = 261
** INFO: <bus_callback:232>: Pipeline runningJPEG parameter struct mismatch: library thinks size is 728, caller expects 720
GPUassert: driver shutting down /dvs/git/dirty/git-master_linux/deepstream/sdk/src/utils/nvmultiobjecttracker/src/modules/NvMultiObjectTracker/context.cpp 196
Segmentation fault (core dumped)
when trying to initialize this code:
obj_ctx_handle_ = nvds_obj_enc_create_context(gpu_id_);
deepstream-transfer-learning-app/image_meta_consumer.cpp
This is my config file:
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=5
[tiled-display]
enable=0
rows=1
columns=1
width=1280
height=720
gpu-id=0
nvbuf-memory-type=0
[source0]
enable=1
type=3
uri=file:///home/drivelensai/DeepStream-Yolo/videos/test.mp4
num-sources=1
gpu-id=0
cudadec-memtype=0
[sink0]
enable=1
type=1
sync=0
gpu-id=0
nvbuf-memory-type=0
[sink1]
enable=0 # Enable file saving
type=4 # File sink
container=2 # MP4 format
codec=1 # H.264 encoding
bitrate=2000000 # Bitrate for quality
enc-type=1 # Use hardware encoder
output-file=/home/drivelensai/DeepStream-Yolo/output.mkv # File location
sync=0 # Set to 1 for real-time sync, 0 for faster processing
source-id=0
[sink2]
enable=1
sync=0
# source-id=0
# msg-conv-broker-on-demux=1
#Type - 1=FakeSink 2=EglSink 3=File 4=UDPSink 5=nvoverlaysink 6=MsgConvBroker
type=6
msg-conv-config=config_msgconv.txt
#(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
msg-conv-payload-type=1
#(0): Create payload using NvdsEventMsgMeta
#(1): New Api to create payload using NvDsFrameMeta
msg-conv-msg2p-new-api=1
#Frame interval at which payload is generated
msg-conv-frame-interval=1
msg-conv-msg2p-lib=sources/libs/nvmsgconv/libnvds_msgconv.so
msg-broker-proto-lib=/opt/nvidia/deepstream/deepstream/lib/libnvds_kafka_proto.so
#Provide your msg-broker-conn-str here
msg-broker-conn-str=localhost;9092
topic=orin_test
#Optional:
msg-broker-config=config_nvmsgbroker.txt
#(0) Use message adapter library api's
#(1) Use new msgbroker library api's
new-api=1
[osd]
enable=1
gpu-id=0
border-width=5
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
[img-save]
enable=1
gpu-id=0
save-img-full-frame=1
save-img-cropped-obj=0
frame-to-skip-rules-path=./test_frames/test.csv
output-folder-path=./test_frames
[streammux]
gpu-id=0
live-source=0
batch-size=1
batched-push-timeout=40000
width=1920
height=1080
enable-padding=0
nvbuf-memory-type=0
[primary-gie]
enable=1
gpu-id=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary_yoloV8.txt
[tracker]
enable=1
gpu-id=0
# For NvDCF and DeepSORT tracker, tracker-width and tracker-height must be a multiple of 32, respectively
tracker-width=640
tracker-height=384
ll-lib-file=/opt/nvidia/deepstream/deepstream-6.3/lib/libnvds_nvmultiobjecttracker.so
# ll-config-file required to set different tracker types
# ll-config-file=config_tracker_IOU.yml
# ll-config-file=config_tracker_NvDCF_perf.yml
ll-config-file=config_tracker_NvDCF_accuracy.yml
# ll-config-file=config_tracker_DeepSORT.yml
display-tracking-id=1
[secondary-gie]
enable=1
model-engine-file=weights/Secondary/traffic_sign_classification_fp16.engine
config-file=config_infer_secondary_yolov11.txt
gie-unique-id=2
operate-on-gie-id=1
[tests]
file-loop=0
I found similar issues looks like mine but I am not understanding how they solved their issue.
Tried: