I have Deepstream-5.0 docker instance with, docker run --gpus all -it --rm -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY -w /opt/nvidia/deepstream/deepstream-5.0/ nvcr.io/nvidia/deepstream:5.0.1-20.09-triton
And when i tried to integrate my YOLO tensorrt engine file with deepstream, i am getting the following error,
** ERROR: <main:655>: Failed to set pipeline to PAUSED
Quitting
App run failed
I am attaching the config files below. I am running, deepstream-app -c deepstream_app_config_yoloV3.txt inside the docker and seeing the above error…
Hi @jazeel.jk ,
1, Could you share the setup info as other topic does?
2. I tried the docker, comamnd and the files, and then got below failure
# deepstream-app -c deepstream_app_config_yoloV3.txt
2021-01-25 14:21:31.566599: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.2
** ERROR: <parse_labels_file:263>: Failed to open label file ‘/root/ds/yolov3_labels.txt’:No such file or directory
** ERROR: <parse_gie:1193>: Failed while parsing label file ‘/root/ds/yolov3_labels.txt’
** ERROR: <parse_gie:1210>: parse_gie failed
** ERROR: <parse_config_file:513>: parse_config_file failed
** ERROR: main:627: Failed to parse config file ‘deepstream_app_config_yoloV3.txt’
Quitting
App run failed
if you can’t share the repo, please share the complete log.
Hi @mchi,
I am using deepstream-5.0 docker container in my linux laptop and i am having cuda 10.2. I have a yolo trained tensorrt engine file which is trained with nvidia transfer learning toolkit…
I want to integrate that trt engine with deepstream. I am using the config files shared above.
source type i given as 1, as i want to use my inbuilt webcam for the input video. And i have used sink type 2…
root@7bf5cf1e9d6f:/opt/nvidia/deepstream/deepstream-5.0/samples/streams# deepstream-app -c deepstream_app_config_yoloV3.txt
** ERROR: <main:655>: Failed to set pipeline to PAUSED
Quitting
App run failed
root@7bf5cf1e9d6f:/opt/nvidia/deepstream/deepstream-5.0/samples/streams#
This is the complete log i am receiving. Any help would be appreciable. Thank you…