Problem with How to ./autogen.sh PYTHON=python3

Please provide complete information as applicable to your setup.

• Hardware Platform (Jetson / GPU) GPU - Geforce RTX 3060
• DeepStream Version 7.1
• JetPack Version (valid for Jetson only)
• TensorRT Version
• NVIDIA GPU Driver Version (valid for GPU only) 550
• Issue Type( questions, new requirements, bugs) 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)
• Requirement details( This is for new requirement. Including the module name-for which plugin or for which sample application, the function description)

Hi, I am trying to run deepstream-test2. I started my container like this

docker run -it --gpus all -v “/home/****/videos_3:/videos” -v /usr/local/cuda:/usr/local/cuda nvcr.io/nvidia/deepstream:7.1-gc-triton-devel bash

Then, I am first trying to follow the How to indications:

At the Prerrequisites area, I am trying to follow this:

   $ sudo apt-get install python-gi-dev
   $ export GST_LIBS="-lgstreamer-1.0 -lgobject-2.0 -lglib-2.0"
   $ export GST_CFLAGS="-pthread -I/usr/include/gstreamer-1.0 -I/usr/include/glib-2.0 -I/usr/lib/x86_64-linux-gnu/glib-2.0/include"
   $ git clone https://github.com/GStreamer/gst-python.git
   $ cd gst-python
   $ git checkout 5343aeb
   $ ./autogen.sh PYTHON=python3
   $ ./configure PYTHON=python3
   $ make
   $ sudo make install

As I reach this instruction

./autogen.sh PYTHON=python3

I am getting the following errors and cannot continue. Thanks for any help you can provide!!

configure.ac:51: warning: The macro AC_PROG_CC_STDC' is obsolete. configure.ac:82: warning: The macro AC_FD_CC’ is obsolete.
configure.ac:95: warning: The macro AC_TRY_CPP' is obsolete. configure.ac:100: warning: The macro AC_HELP_STRING’ is obsolete.
configure.ac:130: warning: The macro AC_HELP_STRING' is obsolete. configure.ac:134: warning: The macro AC_HELP_STRING’ is obsolete.
configure.ac:145: warning: AC_OUTPUT should be used without arguments.

configure: WARNING: unrecognized options: --enable-gtk-doc

configure.ac:47: error: required file ‘./ltmain.sh’ not found

configure: error: Python libs not found. Windows requires Python modules to be explicitly linked to libpython.
configure failed

xhost +

docker run --gpus all -it  --net=host --privileged -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=$DISPLAY -w /opt/nvidia/deepstream/deepstream nvcr.io/nvidia/deepstream:7.1-gc-triton-devel 

./user_deepstream_python_apps_install.sh -b -r v1.2.0

python3 deepstream_test_2.py /opt/nvidia/deepstream/deepstream/samples/streams/sample_720p.h264 
1 Like

Unbelieveble. Thanks so much!

The solution stopped working for a while but after rebooting my system it is working again. In case this information is helpful to someone

You can commit the current container to a new docker image. This is some of the features of docker.

Oh, that is great. Thank you!

I cannot make yolo v8 work as the detector instead of ResNet, to compare them for my video inside of DeepStream. I have imported to my container yolov8n.onnx and labels.txt and tried some changes in dstest2_pgie_config.txt:

[property]

gpu-id=0

net-scale-factor=0.00392156862745098

onnx-file=yolov8n.onnx

model-engine-file=yolov8n.engine

labelfile-path=labels.txt

batch-size=1

process-mode=1

model-color-format=0

0=FP32, 1=INT8, 2=FP16 mode

network-mode=0

num-detected-classes=80

interval=0

gie-unique-id=1

#scaling-filter=0

#scaling-compute-hw=0

cluster-mode=2

custom-lib-path=/opt/nvidia/deepstream/deepstream-7.1/sources/deepstream_python_apps/apps/deepstream-test2/DeepStream-Yolo/nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so

parse-bbox-func-name=NvDsInferParseYoloV8

[class-attrs-all]

pre-cluster-threshold=0.2

topk=20

nms-iou-threshold=0.5

I have also downloaded this repository GitHub - marcoslucianops/DeepStream-Yolo: NVIDIA DeepStream SDK 7.1 / 7.0 / 6.4 / 6.3 / 6.2 / 6.1.1 / 6.1 / 6.0.1 / 6.0 / 5.1 implementation for YOLO models, checked version compatibility (CUDA 12.6, TensorRT 10.3.0.26) and edited the Makefile to include the proper version of deepstream.

But this seems not to be enough and I am getting errors when trying to process a video that was running correctly in deepstream-test2 before I started trying to set yolo as my detector:

nvinfer gstnvinfer.cpp:914:gst_nvinfer_start: error: Config file path: dstest2_pgie_config.txt, NvDsInfer Error: NVDSINFER_CUSTOM_LIB_FAILED

Error: gst-resource-error-quark: Failed to create NvDsInferContext instance (1): gstnvinfer.cpp(914): gst_nvinfer_start (): /GstPipeline:pipeline0/GstNvInfer:primary-inference:

Config file path: dstest2_pgie_config.txt, NvDsInfer Error: NVDSINFER_CUSTOM_LIB_FAILED

[NvMultiObjectTracker] De-initialized

I do not know if this kind of question should be addressed in here, but anyway thanks again for all help provided.

This problem is caused by an incorrect path in the configuration file. Please check the configuration file.

Also, please open a new topic to discuss this issue. thanks

1 Like

Ok. Thank you!