Unsupported operation _MultilevelCropAndResize_TRT (and a few others)

Accelerated Computing Intelligent Video Analytics DeepStream SDK
1

I’m trying to run PeopleSegNet (from Tao toolkit with Deepstream), I got this error.

wsadmin@AIML1001:/opt/nvidia/deepstream/deepstream/samples/configs/tao_pretrained_models$ sudo deepstream-app -c deepstream_app_source1_segmentation.txt

 *** DeepStream: Launched RTSP Streaming at rtsp://localhost:8554/ds-test ***

gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
gstnvtracker: Batch processing is ON
gstnvtracker: Past frame output is ON
[NvMultiObjectTracker] Initialized
WARNING: ../nvdsinfer/nvdsinfer_model_builder.cpp:1482 Deserialize engine failed because file path: /opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt_b1_gpu0_int8.engine open error
0:00:00.814698376 541174 0x559916138120 WARN                 nvinfer gstnvinfer.cpp:643:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:1888> [UID = 1]: deserialize engine from file :/opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt_b1_gpu0_int8.engine failed
0:00:00.829914802 541174 0x559916138120 WARN                 nvinfer gstnvinfer.cpp:643:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:1993> [UID = 1]: deserialize backend context from engine from file :/opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt_b1_gpu0_int8.engine failed, try rebuild
0:00:00.829937044 541174 0x559916138120 INFO                 nvinfer gstnvinfer.cpp:646:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1914> [UID = 1]: Trying to create engine from model files
ERROR: [TRT]: UffParser: Validator error: pyramid_crop_and_resize_box: Unsupported operation _MultilevelCropAndResize_TRT
parseModel: Failed to parse UFF model
ERROR: tlt/tlt_decode.cpp:358 Failed to build network, error in model parsing.
ERROR: ../nvdsinfer/nvdsinfer_model_builder.cpp:723 Failed to create network using custom network creation function
ERROR: ../nvdsinfer/nvdsinfer_model_builder.cpp:789 Failed to get cuda engine from custom library API
0:00:01.283208569 541174 0x559916138120 ERROR                nvinfer gstnvinfer.cpp:640:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1934> [UID = 1]: build engine file failed
Segmentation fault

• Hardware Platform (Jetson / GPU) GeForce RTX 3090
• DeepStream Version 6.1.0
• TensorRT Version 8.2.5.1-1+cuda11.4
• NVIDIA GPU Driver Version (valid for GPU only) 470.103.01
• Issue Type( questions, new requirements, bugs) questions or bugs
• How to reproduce the issue ? (This is for bugs. Including which sample app is using, the configuration files content, the command line used and other details for reproducing) sudo deepstream-app -c deepstream_app_source1_segmentation.txt
• CUDA Version : 11.4
• CUDNN Version : 8.4.0.27-1+cuda11.6
• Operating System : Ubuntu 20.04
• Python Version : 3.8.10 (default, Mar 15 2022, 12:22:08) [GCC 9.4.0]
• Tensorflow Version : 2.7.0

Relevant files

Config file (deepstream_app_source1_segmentation.txt)

[application]
enable-perf-measurement=1
perf-measurement-interval-sec=1

[tiled-display]
enable=1
rows=1
columns=1
width=960
height=540
gpu-id=0

[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=2
num-sources=1
uri=file://../../streams/sample_qHD.mp4
gpu-id=0

[streammux]
gpu-id=0
batch-size=1
batched-push-timeout=40000
## Set muxer output width and height
width=960
height=540

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

[osd]
enable=1
gpu-id=0
border-width=3
text-size=15
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Serif
display-mask=1
display-bbox=0
display-text=0

[primary-gie]
enable=1
gpu-id=0
# Modify as necessary
batch-size=1
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
gie-unique-id=1
# Replace the infer primary config file when you need to
# use other detection models
# model-engine-file=../../models/tao_pretrained_models/mrcnn/mask_rcnn_resnet50.etlt_b1_gpu0_int8.engine
config-file=config_infer_primary_peopleSegNet.txt

[sink1]
enable=1
type=3
#1=mp4 2=mkv
container=1
#1=h264 2=h265 3=mpeg4
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=0
bitrate=2000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
output-file=out.mp4
source-id=0

[sink2]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming 5=Overlay
type=4
#1=h264 2=h265
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=0
bitrate=4000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
# set below properties in case of RTSPStreaming
rtsp-port=8554
udp-port=5400

[tracker]
enable=1
# 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/lib/libnvds_nvmultiobjecttracker.so
# ll-config-file required to set different tracker types
# ll-config-file=../deepstream-app/config_tracker_IOU.yml
ll-config-file=../deepstream-app/config_tracker_NvDCF_perf.yml
# ll-config-file=../deepstream-app/config_tracker_NvDCF_accuracy.yml
# ll-config-file=../deepstream-app/config_tracker_DeepSORT.yml
gpu-id=0
enable-batch-process=1
enable-past-frame=1
display-tracking-id=1

[tests]
file-loop=0

I am running into a similar issue for the detection model (deepstream_app_source1_detection_models.txt)
Here is the output for the detection model:

wsadmin@AIML1001:/opt/nvidia/deepstream/deepstream/samples/configs/tao_pretrained_models$ sudo deepstream-app -c deepstream_app_source1_detection_models.txt
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream/lib/libnvds_nvmultiobjecttracker.so
gstnvtracker: Batch processing is ON
gstnvtracker: Past frame output is ON
[NvMultiObjectTracker] Initialized
0:00:00.203878513  2716 0x7f65a00022f0 WARN                 nvinfer gstnvinfer.cpp:643:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::initialize() <nvdsinfer_context_impl.cpp:1161> [UID = 1]: Warning, OpenCV has been deprecated. Using NMS for clustering instead of cv::groupRectangles with topK = 20 and NMS Threshold = 0.5
WARNING: ../nvdsinfer/nvdsinfer_model_builder.cpp:1482 Deserialize engine failed because file path: /opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/ssd/ssd.etlt_b1_gpu0_int8.engine open error
0:00:00.793476196  2716 0x7f65a00022f0 WARN                 nvinfer gstnvinfer.cpp:643:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:1888> [UID = 1]: deserialize engine from file :/opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/ssd/ssd.etlt_b1_gpu0_int8.engine failed
0:00:00.808188616  2716 0x7f65a00022f0 WARN                 nvinfer gstnvinfer.cpp:643:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:1993> [UID = 1]: deserialize backend context from engine from file :/opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/ssd/ssd.etlt_b1_gpu0_int8.engine failed, try rebuild
0:00:00.808211489  2716 0x7f65a00022f0 INFO                 nvinfer gstnvinfer.cpp:646:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1914> [UID = 1]: Trying to create engine from model files
ERROR: [TRT]: UffParser: Validator error: FirstDimTile_4: Unsupported operation _BatchTilePlugin_TRT
parseModel: Failed to parse UFF model
ERROR: tlt/tlt_decode.cpp:358 Failed to build network, error in model parsing.
ERROR: ../nvdsinfer/nvdsinfer_model_builder.cpp:723 Failed to create network using custom network creation function
ERROR: ../nvdsinfer/nvdsinfer_model_builder.cpp:789 Failed to get cuda engine from custom library API
0:00:01.187606492  2716 0x7f65a00022f0 ERROR                nvinfer gstnvinfer.cpp:640:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1934> [UID = 1]: build engine file failed
Segmentation fault

And here’s the config file for deepstream_app_source1_detection_models.txt:

[application]
enable-perf-measurement=1
perf-measurement-interval-sec=1

[tiled-display]
enable=1
rows=1
columns=1
width=1280
height=720
gpu-id=0

[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=3
num-sources=1
uri=file://../../streams/sample_1080p_h265.mp4
gpu-id=0

[streammux]
gpu-id=0
batch-size=1
batched-push-timeout=40000
## Set muxer output width and height
width=1920
height=1080

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

[osd]
enable=1
gpu-id=0
border-width=3
text-size=15
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Arial

[primary-gie]
enable=1
gpu-id=0
# Modify as necessary
batch-size=1
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
gie-unique-id=1
# Replace the infer primary config file when you need to
# use other detection models
#config-file=config_infer_primary_frcnn_dgpu.txt
#config-file=config_infer_primary_frcnn_jetson.txt
config-file=config_infer_primary_ssd.txt
#config-file=config_infer_primary_dssd.txt
#config-file=config_infer_primary_retinanet.txt
#config-file=config_infer_primary_yolov3_dgpu.txt
#config-file=config_infer_primary_yolov3_jetson.txt
#config-file=config_infer_primary_yolov4_dgpu.txt
#config-file=config_infer_primary_yolov4_jetson.txt
#config-file=config_infer_primary_detectnet_v2.txt
#config-file=config_infer_primary_yolov4-tiny_dgpu.txt
#config-file=config_infer_primary_yolov4-tiny_jetson.txt
#config-file=config_infer_primary_efficientdet.txt

[sink1]
enable=0
type=3
#1=mp4 2=mkv
container=1
#1=h264 2=h265 3=mpeg4
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=0
bitrate=2000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
output-file=out.mp4
source-id=0

[sink2]
enable=0
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming 5=Overlay
type=4
#1=h264 2=h265
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=0
bitrate=4000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
# set below properties in case of RTSPStreaming
rtsp-port=8554
udp-port=5400

[tracker]
enable=1
# 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/lib/libnvds_nvmultiobjecttracker.so
# ll-config-file required to set different tracker types
# ll-config-file=../deepstream-app/config_tracker_IOU.yml
ll-config-file=../deepstream-app/config_tracker_NvDCF_perf.yml
# ll-config-file=../deepstream-app/config_tracker_NvDCF_accuracy.yml
# ll-config-file=../deepstream-app/config_tracker_DeepSORT.yml
gpu-id=0
enable-batch-process=1
enable-past-frame=1
display-tracking-id=1

[tests]
file-loop=0

By the way, running PeopleNet worked without problems.

3

Can you share you nvinfer configure? Do you have any change based on DS 6.1 release?

4

I don’t recall changing anything in that config

mher@AIML1001:/opt/nvidia/deepstream/deepstream/samples/configs/tao_pretrained_models$ cat config_infer_primary_peopleSegNet.txt
################################################################################
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
################################################################################

[property]
gpu-id=0
net-scale-factor=0.017507
offsets=123.675;116.280;103.53
model-color-format=0
tlt-model-key=nvidia_tlt
tlt-encoded-model=../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt
model-engine-file=../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt_b1_gpu0_int8.engine
network-type=3 ## 3 is for instance segmentation network
labelfile-path=./peopleSegNet_labels.txt
int8-calib-file=../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50_int8.txt
infer-dims=3;576;960
num-detected-classes=2
uff-input-blob-name=Input
batch-size=1
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=1
interval=0
gie-unique-id=1
#no cluster
## 1=DBSCAN, 2=NMS, 3= DBSCAN+NMS Hybrid, 4 = None(No clustering)
## MRCNN supports only cluster-mode=4; Clustering is done by the model itself
cluster-mode=4
output-instance-mask=1
output-blob-names=generate_detections;mask_fcn_logits/BiasAdd
parse-bbox-instance-mask-func-name=NvDsInferParseCustomMrcnnTLTV2
custom-lib-path=/opt/nvidia/deepstream/deepstream/lib/libnvds_infercustomparser.so

[class-attrs-all]
pre-cluster-threshold=0.8
5

Can you have a try with below which list in the /opt/nvidia/deepstream/deepstream/samples/configs/tao_pretrained_models/README.md

  • For instance segmentation models(MaskRCNN/peopelSegNet), use deepstream_app_source1_mrcnn.txt
6

When I tried running the mrcnn:

wsadmin@AIML1001:/opt/nvidia/deepstream/deepstream/samples/configs/tao_pretrained_models$ sudo deepstream-app -c deepstream_app_source1_mrcnn.txt
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream-6.0/lib/libnvds_nvmultiobjecttracker.so
gstnvtracker: Failed to open low-level lib at /opt/nvidia/deepstream/deepstream-6.0/lib/libnvds_nvmultiobjecttracker.so
 dlopen error: /opt/nvidia/deepstream/deepstream-6.0/lib/libnvds_nvmultiobjecttracker.so: cannot open shared object file: No such file or directory
gstnvtracker: Failed to initilaize low level lib.
** ERROR: <main:716>: Failed to set pipeline to PAUSED
Quitting
App run failed

I looked up this issue and one moderator had suggested to run gst-inspect-1.0 nvinfer, so I did and got this output:
No such element or plugin 'nvinfer'

After this, I realized that the error had something to do with the tracker so i disabled it in the deepstream_app_source1_mrcnn.txt config file:

[application]
enable-perf-measurement=1
perf-measurement-interval-sec=1

[tiled-display]
enable=1
rows=1
columns=1
width=960
height=540
gpu-id=0

[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=3
num-sources=1
uri=file://../../streams/sample_qHD.mp4
gpu-id=0

[streammux]
gpu-id=0
batch-size=1
batched-push-timeout=40000
## Set muxer output width and height
width=960
height=540

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

[osd]
enable=1
gpu-id=0
border-width=3
text-size=15
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Serif
display-mask=1
display-bbox=0
display-text=0

[primary-gie]
enable=1
gpu-id=0
# Modify as necessary
batch-size=1
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
gie-unique-id=1
# Replace the infer primary config file when you need to
# use other detection models
# model-engine-file=../../models/tao_pretrained_models/mrcnn/mask_rcnn_resnet50.etlt_b1_gpu0_int8.engine
config-file=config_infer_primary_peopleSegNet.txt

[sink1]
enable=1
type=3
#1=mp4 2=mkv
container=1
#1=h264 2=h265 3=mpeg4
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=0
bitrate=2000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
output-file=out.mp4
source-id=0

[sink2]
enable=0
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming 5=Overlay
type=4
#1=h264 2=h265
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=0
bitrate=4000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
# set below properties in case of RTSPStreaming
rtsp-port=8554
udp-port=5400

[tracker]
enable=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-6.0/lib/libnvds_nvmultiobjecttracker.so
# ll-config-file required to set different tracker types
# ll-config-file=../deepstream-app/config_tracker_IOU.yml
ll-config-file=../deepstream-app/config_tracker_NvDCF_perf.yml
# ll-config-file=../deepstream-app/config_tracker_NvDCF_accuracy.yml
# ll-config-file=../deepstream-app/config_tracker_DeepSORT.yml
gpu-id=0
enable-batch-process=1
enable-past-frame=1
display-tracking-id=1

[tests]
file-loop=0

After this change i ran sudo deepstream-app -c deepstream_app_source1_mrcnn.txt again and got this instead:

WARNING: ../nvdsinfer/nvdsinfer_model_builder.cpp:1482 Deserialize engine failed because file path: /opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt_b1_gpu0_int8.engine open error
0:00:00.779937490 15464 0x55fffdc30780 WARN                 nvinfer gstnvinfer.cpp:643:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:1888> [UID = 1]: deserialize engine from file :/opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt_b1_gpu0_int8.engine failed
0:00:00.794853098 15464 0x55fffdc30780 WARN                 nvinfer gstnvinfer.cpp:643:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Warning from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:1993> [UID = 1]: deserialize backend context from engine from file :/opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/../../models/tao_pretrained_models/peopleSegNet/V2/peoplesegnet_resnet50.etlt_b1_gpu0_int8.engine failed, try rebuild
0:00:00.794875210 15464 0x55fffdc30780 INFO                 nvinfer gstnvinfer.cpp:646:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1914> [UID = 1]: Trying to create engine from model files
ERROR: [TRT]: UffParser: Validator error: pyramid_crop_and_resize_box: Unsupported operation _MultilevelCropAndResize_TRT
parseModel: Failed to parse UFF model
ERROR: tlt/tlt_decode.cpp:358 Failed to build network, error in model parsing.
ERROR: ../nvdsinfer/nvdsinfer_model_builder.cpp:723 Failed to create network using custom network creation function
ERROR: ../nvdsinfer/nvdsinfer_model_builder.cpp:789 Failed to get cuda engine from custom library API
0:00:01.238895218 15464 0x55fffdc30780 ERROR                nvinfer gstnvinfer.cpp:640:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1934> [UID = 1]: build engine file failed
Segmentation fault

This is the same error as in the topmost post

7

Please check latest /opt/nvidia/deepstream/deepstream-6.1/samples/configs/tao_pretrained_models/README.md after git clone. Please follow the guide of README.md and use deepstream_app_source1_segmentation.txt.

8

I did

9

Do you upgrade TRT plugin lib based on the guide in the README?

- https://github.com/NVIDIA-AI-IOT/deepstream_tao_apps/tree/master/TRT-OSS/Jetson for Jetson

- https://github.com/NVIDIA-AI-IOT/deepstream_tao_apps/tree/master/TRT-OSS/x86 for x86
10

I tried doing this, on the second step (as the readme suggested) in the end when running $HOME/install/bin/cmake .. -DGPU_ARCHS=86 -DTRT_LIB_DIR=/usr/lib/x86_64-linux-gnu/ -DCMAKE_C_COMPILER=/ I encountered an error.

[Couldn’t find CUDA library root. · Issue #65] (Couldn't find CUDA library root. · Issue #65 · NVIDIA-AI-IOT/deepstream_tao_apps · GitHub)

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Solved this by following Option 2 (lookout for some variation of versions, specify yours as needed) of the prerequisite guide in the readme

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