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Copy file name to clipboardExpand all lines: FAQ.md
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# Frequently Asked Questions and Troubleshooting Guide
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*[Git clone fails due to Gstreamer repo access error](#faq9)
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*[Application fails to work with mp4 stream](#faq0)
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*[Ctrl-C does not stop the app during engine file generation](#faq1)
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*[Application fails to create gst elements](#faq2)
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*[Error on setting string field](#faq5)
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*[Pipeline unable to perform at real time](#faq6)
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*[Triton container problems with multi-GPU setup](#faq7)
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*[ModuleNotFoundError: No module named 'pyds'] (#faq8)
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*[ModuleNotFoundError: No module named 'pyds'](#faq8)
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<aname="faq9"></a>
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### Git clone fails due to Gstreamer repo access error
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If the following error is encountered while cloning:
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```
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fatal: unable to access 'https://gitlab.freedesktop.org/gstreamer/common.git/': server certificate verification failed. CAfile: /etc/ssl/certs/ca-certificates.crt CRLfile: none
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fatal: clone of 'https://gitlab.freedesktop.org/gstreamer/common.git' into submodule path '/opt/nvidia/deepstream/deepstream/sources/ds_python/3rdparty/gst-python/common' failed
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```
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Temporarily disable git SSL verification by:
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```
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export GIT_SSL_NO_VERIFY=true
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```
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before cloning the repo. Unset the variable after cloning.
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<aname="faq0"></a>
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### Application fails to work with mp4 stream
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<aname="faq8"></a>
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### ModuleNotFoundError: No module named 'pyds'
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The pyds extension is installed under /opt/nvidia/deepstream/deepstream/lib
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The sample applications all include this path via the is_aarch_64 module.
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A setup.py is also provided to install this extension into standard path.
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Currently this needs to be run manually:
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$ cd /opt/nvidia/deepstream/deepstream/lib
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$ python3 setup.py install
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The pyds wheel installs the pyds.so library where all the pip packages are stored. Make sure the wheel installation succeeds and the pyds.so is present in the correct path (which should be /home/<user>/.local/lib/python<python-version>/site-packages/pyds.so)
Go into each app directory and follow instructions in the README.
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DeepStream MetaData contains inference results and other information used in analytics. The MetaData is attached to the Gst Buffer received by each pipeline component. The metadata format is described in detail in the [SDK MetaData documentation](https://docs.nvidia.com/metropolis/deepstream/dev-guide/text/DS_plugin_metadata.html) and [API Guide](https://docs.nvidia.com/metropolis/deepstream/python-api/index.html).
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The SDK MetaData library is developed in C/C++. Python bindings provide access to the MetaData from Python applications. The bindings are provided in a compiled module, available for x86_64 and Jetson platforms. This module, pyds.so, is available as part of the DeepStream SDK installation under <DeepStreamRoot>/lib directory.
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The SDK MetaData library is developed in C/C++. Python bindings provide access to the MetaData from Python applications. The bindings are provided as part of this repository [here](bindings) and can be compiled natively for x86_64 and Jetson platforms. This module, pyds.so, can also be cross-compiled for aarch64 on x86 host by using [Qemu](https://www.qemu.org/) emulator. Dockerfile for the cross-compilation is provided [here](bindings/qemu_docker/ubuntu-cross-aarch64.Dockerfile)
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The sample applications gets the import path for this module through common/utils.py. A setup.py is also included for installing the module into standard path:
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cd /opt/nvidia/deepstream/deepstream/lib
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<aname="imagedata_access"></a>
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## Image Data Access
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Decoded images are accessible as NumPy arrays via the `get_nvds_buf_surface` function. This function is documented in the [API Guide](https://docs.nvidia.com/metropolis/deepstream/5.1/python-api/index.html).
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Decoded images are accessible as NumPy arrays via the `get_nvds_buf_surface` function. This function is documented in the [API Guide](https://docs.nvidia.com/metropolis/deepstream/6.0/python-api/index.html).
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Please see the [deepstream-imagedata-multistream](apps/deepstream-imagedata-multistream) sample application for an example of image data usage.
Copy file name to clipboardExpand all lines: README.md
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This repository contains Python bindings and sample applications for the [DeepStream SDK](https://developer.nvidia.com/deepstream-sdk).
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SDK version supported: 5.1
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SDK version supported: 6.0
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<b>NEW: The bindings sources along with build instructions are now available under [bindings](bindings)! </b>
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Download the latest release package complete with bindings and sample applications from the [release section](../../releases).
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Please report any issues or bugs on the [Deepstream SDK Forums](https://devtalk.nvidia.com/default/board/209).
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Please report any issues or bugs on the [DeepStream SDK Forums](https://devtalk.nvidia.com/default/board/209). This enables the DeepStream community to find help at a central location.
DeepStream pipelines can be constructed using Gst Python, the GStreamer framework's Python bindings. For accessing DeepStream MetaData,
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Python bindings are provided in the form of a compiled module which is included in the DeepStream SDK. This module is generated using [Pybind11](https://github.com/pybind/pybind11).
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Python [bindings](bindings) are provided as part of this repository. This module is generated using [Pybind11](https://github.com/pybind/pybind11).
These bindings support a Python interface to the MetaData structures and functions. Usage of this interface is documented in the [HOW-TO Guide](HOWTO.md) and demonstrated in the sample applications.
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This release adds bindings for decoded image buffers (NvBufSurface) as well as inference output tensors (NvDsInferTensorMeta).
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<aname="sample_applications"></a>
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## Sample Applications
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*[deepstream-test1-usbcam](apps/deepstream-test1-usbcam) -- deepstream-test1 pipelien with USB camera input
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*[deepstream-test1-rtsp-out](apps/deepstream-test1-rtsp-out) -- deepstream-test1 pipeline with RTSP output
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*[deepstream-opticalflow](apps/deepstream-opticalflow) -- optical flow and visualization pipeline with flow vectors returned in NumPy array
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*[deepstream-segmentation](apps/deepstream-segmentation) -- segmentation and visualization pipeline with segmentation mask returned in NumPy array
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*[deepstream-nvdsanalytics](apps/deepstream-nvdsanalytics) -- multistream pipeline with analytics plugin
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*[runtime_source_add_delete](apps/runtime_source_add_delete) -- add/delete source streams at runtime
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*[deepstream-segmentation](apps/deepstream-segmentation) -- segmentation and visualization pipeline with segmentation mask returned in NumPy array
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*[deepstream-nvdsanalytics](apps/deepstream-nvdsanalytics) -- multistream pipeline with analytics plugin
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*[runtime_source_add_delete](apps/runtime_source_add_delete) -- add/delete source streams at runtime
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*[deepstream-imagedata-multistream-redaction](apps/deepstream-imagedata-multistream-redaction) -- multi-stream pipeline with face detection and redaction (<b>NEW</b>)
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*[deepstream-rtsp-in-rtsp-out](apps/deepstream-rtsp-in-rtsp-out) -- multi-stream pipeline with RTSP input/output (<b>NEW</b>)
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Of these applications, the following have been updated or added in this release:
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* runtime_source_add_delete -- add/delete source streams at runtime
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Detailed application information is provided in each application's subdirectory under [apps](apps).
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