Uncertain or not enough buffers, enabling copy threshold Segmentation fault

Description

I am running DS 6.2 on Jetson Orin. I passed Onnx file in config file. Deepstream could generated engine file successfully but deepstream can’t run the pipeline to start inference and got the following error:

Runtime commands:
        h: Print this help
        q: Quit

        p: Pause
        r: Resume

** INFO: <bus_callback:239>: Pipeline ready

0:00:03.830428023 46006 0xaaab04fe5b00 WARN                 qtdemux qtdemux_types.c:239:qtdemux_type_get: unknown QuickTime node type pasp
0:00:03.830502584 46006 0xaaab04fe5b00 WARN                 qtdemux qtdemux.c:3250:qtdemux_parse_trex:<qtdemux0> failed to find fragment defaults for stream 1
Opening in BLOCKING MODE
0:00:03.866730226 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:4512:gst_v4l2_object_probe_caps:<nvv4l2decoder0:src> Failed to probe pixel aspect ratio with VIDIOC_CROPCAP: Unknown error -1
0:00:03.866778450 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
0:00:03.866804467 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
0:00:03.866824467 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
0:00:03.866842867 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
NvMMLiteOpen : Block : BlockType = 261
NVMEDIA: Reading vendor.tegra.display-size : status: 6
NvMMLiteBlockCreate : Block : BlockType = 261
0:00:03.971916810 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:4512:gst_v4l2_object_probe_caps:<nvv4l2decoder0:src> Failed to probe pixel aspect ratio with VIDIOC_CROPCAP: Unknown error -1
0:00:03.971977931 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
0:00:03.972003787 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
0:00:03.972018476 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
0:00:03.972032524 46006 0xffff040529e0 WARN                    v4l2 gstv4l2object.c:2398:gst_v4l2_object_add_interlace_mode:0xfffefc01a010 Failed to determine interlace mode
0:00:03.974525521 46006 0xffff040529e0 WARN            v4l2videodec gstv4l2videodec.c:1880:gst_v4l2_video_dec_decide_allocation:<nvv4l2decoder0> Duration invalid, not setting latency
** INFO: <bus_callback:225>: Pipeline running

0:00:03.978452555 46006 0xffff040529e0 WARN          v4l2bufferpool gstv4l2bufferpool.c:1114:gst_v4l2_buffer_pool_start:<nvv4l2decoder0:pool:src> Uncertain or not enough buffers, enabling copy threshold
NvMMLiteOpen : Block : BlockType = 4
===== NVMEDIA: NVENC =====
NvMMLiteBlockCreate : Block : BlockType = 4
0:00:04.004423148 46006 0xffff0800a180 WARN          v4l2bufferpool gstv4l2bufferpool.c:1565:gst_v4l2_buffer_pool_dqbuf:<nvv4l2decoder0:pool:src> Driver should never set v4l2_buffer.field to ANY
0:00:04.005385147 46006 0xaaaae8daf1e0 WARN          v4l2bufferpool gstv4l2bufferpool.c:1114:gst_v4l2_buffer_pool_start:<sink_sub_bin_encoder1:pool:src> Uncertain or not enough buffers, enabling copy threshold
Segmentation fault

Environment

TensorRT Version: 8.5.2-1+cuda11.4
GPU Type: Jetson Orin
Nvidia Driver Version: Jetson Orin
CUDA Version: 11.4
CUDNN Version: 8.6.0.166-1+cuda11.4 arm64
Operating System + Version: Ubuntu 20.04
Python Version (if applicable): NA
TensorFlow Version (if applicable): NA
PyTorch Version (if applicable): NA
Baremetal or Container (if container which image + tag): Baremetal

Steps To Reproduce

$ Deepstream-app -c deepstream-app-config.txt

$ cat deepstream-app-config.txt

[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:///opt/nvidia/deepstream/deepstream/samples/streams/sample_720p.mp4
ream.mp4
num-sources=1
gpu-id=0
cudadec-memtype=0

[sink0]
enable=0
type=2
sync=0
gpu-id=0
nvbuf-memory-type=0

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

[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

[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_yoloV5.txt

[tests]
file-loop=0

config_infer_primary_yoloV5.txt:

[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
onnx-file=yolov5lv6.1_img640_class9.onnx
model-engine-file=yolov5lv6.1_img640_class9_fp16.engine
#int8-calib-file=calib.table
labelfile-path=labels.txt
batch-size=1 # number of frames for inference
network-mode=2 # 0:fp32 1:int8 2:fp16
num-detected-classes=9
interval=0
gie-unique-id=1 
process-mode=1 # 1:primary 2:secondary 
network-type=0 # 0:detector 1: classifier
cluster-mode=2 # 2: NMS 
maintain-aspect-ratio=1
symmetric-padding=1
#force-implicit-batch-dim=1
#workspace-size=1000
parse-bbox-func-name=NvDsInferParseYolo
#parse-bbox-func-name=NvDsInferParseYoloCuda
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
engine-create-func-name=NvDsInferYoloCudaEngineGet

[class-attrs-all]
nms-iou-threshold=0.45
pre-cluster-threshold=0.25
topk=300

Hi,

We are moving this post to the Deepstream forum to get better help.

Thank you.

Can you provide “yolov5lv6.1_img640_class9.onnx” for debugging?

Why do you use “NvDsInferYoloCudaEngineGet” to generate your engine? What is your modification to it? Your configurations are confusing.

This is of no use since you have set “parse-bbox-func-name=NvDsInferParseYolo”.

There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks

Where and how did you get your “yolov5lv6.1_img640_class9.onnx”?

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