../nvdsinfer/nvdsinfer_func_utils.cpp:33 [TRT] UffParser:

Accelerated Computing Intelligent Video Analytics TAO Toolkit
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1

…/nvdsinfer/nvdsinfer_func_utils.cpp:33 [TRT] UffParser:
My environment: TLT streaming analytics v3.0-dp-py3

My project is face-mask-detection,the model is tlt-experiments/experiment_dir_final/resnet18_detector.etlt

2

Please share your full command and full log.

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root@eab6755afacf:/workspace/tlt-experiments/face-mask-detection/ds_configs_bak# deepstream-app -c deepstream_app_source1_video_masknet_gpu_fp32.txt
gstnvtracker: Loading low-level lib at /opt/nvidia/deepstream/deepstream-5.0/lib/libnvds_mot_klt.so
gstnvtracker: Optional NvMOT_RemoveStreams not implemented
gstnvtracker: Batch processing is OFF
gstnvtracker: Past frame output is OFF
0:00:00.390843582 138 0x55be455dc830 INFO nvinfer gstnvinfer.cpp:619:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1715> [UID = 1]: Trying to create engine from model files
ERROR: …/nvdsinfer/nvdsinfer_func_utils.cpp:33 [TRT]: UffParser: Could not read buffer.
parseModel: Failed to parse UFF model
ERROR: tlt/tlt_decode.cpp:274 failed to build network since parsing model errors.
ERROR: …/nvdsinfer/nvdsinfer_model_builder.cpp:797 Failed to create network using custom network creation function
ERROR: …/nvdsinfer/nvdsinfer_model_builder.cpp:862 Failed to get cuda engine from custom library API
0:00:00.509099443 138 0x55be455dc830 ERROR nvinfer gstnvinfer.cpp:613:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Error in NvDsInferContextImpl::buildModel() <nvdsinfer_context_impl.cpp:1735> [UID = 1]: build engine file failed
Segmentation fault (core dumped)

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the deepstream_app_source1_video_masknet_gpu_fp32.txt 's content as follows:

[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
tlt-model-key=dWRnNjMycGtmMzIwNjI0MjV1aXZtb2xtb2w6OTRiZWFmNjYtNDY5Zi00NDk4LWFhYTktNTkxYWMyOGUyNTlk
tlt-encoded-model=/workspace/tlt-experiments/dataset/experiment_dir_final2/resnet18_detector.etlt
labelfile-path=labels_masknet.txt

infer-dims=3;544;960
uff-input-order=0
uff-input-blob-name=input_1
batch-size=1
model-color-format=0

network-mode=0
#int8-calib-file=/tlt-demo/data/experiment_dir_final/calibration.bin
num-detected-classes=2
cluster-mode=3
interval=0
gie-unique-id=1
is-classifier=0
classifier-threshold=0.9
output-blob-names=output_bbox/BiasAdd;output_cov/Sigmoid

[class-attrs-0]
pre-cluster-threshold=0.3
group-threshold=1
eps=0.5
#minBoxes=1
detected-min-w=0
detected-min-h=0
detected-max-w=0
detected-max-h=0

[class-attrs-1]
pre-cluster-threshold=0.3
group-threshold=1
eps=0.3
#minBoxes=1
detected-min-w=0
detected-min-h=0
detected-max-w=0
detected-max-h=0

5

Please check

  • if tlt-model-key is correct.
  • if the path to tlt-encoded-model is correct