Update to 1.1.11 Release

This release is compatible with DeepStream SDK 7.0

Ubuntu 22.04
Python 3.10
DeepStream SDK 7.0

Features:
- New module platform_info() has been added for checking for WSL, integrated GPU, and aarch64. All apps and integration tests have been updated to use this module when checking for platform. See deepstream_test1 for simple usage.
- SBSA is now supported. Check bindings/README.md for quick build instructions.
- Apps have been updated to use request_pad_simple() instead of the deprecated method get_request_pad(). See gst-python API documentation for details.
- New API nvds_measure_buffer_latency() has been added for pipeline and component latency measurement. See deepstream-test3 app and bindfunctions.cpp for reference.

Author: nv-camilleh

FAQ.md

@@ -165,5 +165,5 @@ The pyds wheel installs the pyds.so library where all the pip packages are store
 
 Command to install the pyds wheel is:
 ```bash
-   $ pip3 install ./pyds-1.1.10-py3-none*.whl
+   $ pip3 install ./pyds-1.1.11-py3-none*.whl
 ```

HOWTO.md

@@ -16,7 +16,7 @@ This guide provides resources for DeepStream application development in Python.
 ## Prerequisites
 
 * Ubuntu 22.04
-* [DeepStream SDK 6.4](https://developer.nvidia.com/deepstream-download) or later
+* [DeepStream SDK 7.0](https://developer.nvidia.com/deepstream-download) or later
 * Python 3.10
 * [Gst Python](https://gstreamer.freedesktop.org/modules/gst-python.html) v1.20.3
 

README.md

@@ -2,20 +2,26 @@
 
 This repository contains Python bindings and sample applications for the [DeepStream SDK](https://developer.nvidia.com/deepstream-sdk).  
 
-SDK version supported: 6.4
+SDK version supported: 7.0
 
-<b>This release only supports Ubuntu 22.04 for DeepStreamSDK 6.4 with Python 3.10 and [gst-python](3rdparty/gst-python/) 1.20.3! Ubuntu 20.04 for DeepStreamSDK 6.3 with Python 3.8 support is NOW DEPRECATED</b>
+<b>This release only supports Ubuntu 22.04 for DeepStreamSDK 7.0 with Python 3.10 and [gst-python](3rdparty/gst-python/) 1.20.3! Ubuntu 20.04 for DeepStreamSDK 6.3 with Python 3.8 support is NOW DEPRECATED</b>
 
-The bindings sources along with build instructions are available under [bindings](bindings)! We include one [guide](bindings/BINDINGSGUIDE.md) for contributing to bindings and another [guide](bindings/CUSTOMUSERMETAGUIDE.md) for advanced use-cases such as writing bindings for custom data structures.
-
-Download the latest release package complete with bindings and sample applications from the [release section](../../releases).  
+The bindings sources along with build instructions are available under [bindings](bindings)! We include one [guide](bindings/BINDINGSGUIDE.md) for contributing to bindings and another [guide](bindings/CUSTOMUSERMETAGUIDE.md) for advanced use-cases such as writing bindings for custom data structures. 
 
 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 Python Apps](#deepstream-python-apps)
+  - [Setup](#setup)
   - [Python Bindings](#python-bindings)
+    - [Python Bindings Breaking API Change](#python-bindings-breaking-api-change)
   - [Sample Applications](#sample-applications)
 
+## Setup
+Once you have DeepStreamSDK pre-requisites and DeepStreamSDK installed on the system, navigate to <DS_ROOT>/sources/ dir which is /opt/nvidia/deepstream/deepstream/sources/ and git clone deepstream_python_apps repo here.
+
+The latest bindings can be installed from [release section](../../releases).
+You can also build the bindings from source using the instructions in the [bindings readme](bindings/README.md) if needed.
+
 <a name="metadata_bindings"></a>
 ## Python Bindings
 
@@ -45,13 +51,13 @@ To run the sample applications or write your own, please consult the [HOW-TO Gui
 
 We currently provide the following sample applications:
 * [deepstream-test1](apps/deepstream-test1) -- 4-class object detection pipeline, also demonstrates support for new nvstreammux
-* **UPDATED** [deepstream-test2](apps/deepstream-test2) -- 4-class object detection, tracking and attribute classification pipeline - now uses new names for tracker meta data types in DS 6.4
+* [deepstream-test2](apps/deepstream-test2) -- 4-class object detection, tracking and attribute classification pipeline
 * [deepstream-test3](apps/deepstream-test3) -- multi-stream pipeline performing 4-class object detection, also supports triton inference server, no-display mode, file-loop and silent mode
-* **UPDATED** [deepstream-test4](apps/deepstream-test4) -- msgbroker for sending analytics results to the cloud - now supports MQTT protocol adaptor
+* [deepstream-test4](apps/deepstream-test4) -- msgbroker for sending analytics results to the cloud
 * [deepstream-imagedata-multistream](apps/deepstream-imagedata-multistream) -- multi-stream pipeline with access to image buffers
 * [deepstream-ssd-parser](apps/deepstream-ssd-parser) -- SSD model inference via Triton server with output parsing in Python
 * [deepstream-test1-usbcam](apps/deepstream-test1-usbcam) -- deepstream-test1 pipeline with USB camera input
-* **UPDATED** [deepstream-test1-rtsp-out](apps/deepstream-test1-rtsp-out) -- deepstream-test1 pipeline with RTSP output - now demonstrates adding software encoder option to support Jetson Orin Nano
+* [deepstream-test1-rtsp-out](apps/deepstream-test1-rtsp-out) -- deepstream-test1 pipeline with RTSP output, demonstrates adding software encoder option to support Jetson Orin Nano
 * [deepstream-opticalflow](apps/deepstream-opticalflow) -- optical flow and visualization pipeline with flow vectors returned in NumPy array
 * [deepstream-segmentation](apps/deepstream-segmentation) -- segmentation and visualization pipeline with segmentation mask returned in NumPy array
 * [deepstream-nvdsanalytics](apps/deepstream-nvdsanalytics) -- multistream pipeline with analytics plugin

apps/README

@@ -20,7 +20,7 @@ DeepStream SDK Python Bindings
 ================================================================================
 Setup pre-requisites:
 - Ubuntu 22.04
-- NVIDIA DeepStream SDK 6.4
+- NVIDIA DeepStream SDK 7.0
 - Python 3.10
 - Gst-python
 
@@ -36,7 +36,7 @@ Package Contents
 Installing Pre-requisites:
 --------------------------------------------------------------------------------
 
-DeepStream SDK 6.4
+DeepStream SDK 7.0
 --------------------
 Download and install from https://developer.nvidia.com/deepstream-download
 
@@ -51,16 +51,23 @@ If missing, install with the following steps:
 $ sudo apt update
 $ sudo apt install python3-gi python3-dev python3-gst-1.0 -y
 
+cuda-python
+-----------
+$ pip3 install cuda-python
+
 --------------------------------------------------------------------------------
 Running the samples
 --------------------------------------------------------------------------------
-The apps are configured to work from inside the DeepStream SDK 6.4 installation.
+The apps are configured to work from inside the DeepStream SDK 7.0 installation.
 
 Clone the deepstream_python_apps repo under <DeepStream ROOT>/sources:
 $ git clone https://github.com/NVIDIA-AI-IOT/deepstream_python_apps
 This will create the following directory:
 <DeepStream ROOT>/sources/deepstream_python_apps
-
+Cuda python APIs are used to distinguish between iGPU and dGPU.
+Install cuda-python using:
+pip3 install cuda-python
+NOTE: is_aarch64.py is deprecated in favor of platform_info.py
 Follow README in each app's directory to run the app.
 
 Example: running test1 app:

apps/common/is_aarch_64.py

@@ -0,0 +1,94 @@
+################################################################################
+# SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+################################################################################
+
+import sys
+import platform
+from threading import Lock
+from cuda import cudart
+from cuda import cuda
+
+guard_platform_info = Lock()
+
+class PlatformInfo:
+    def __init__(self):
+        self.is_wsl_system = False
+        self.wsl_verified = False
+        self.is_integrated_gpu_system = False
+        self.is_integrated_gpu_verified = False
+        self.is_aarch64_platform = False
+        self.is_aarch64_verified = False
+
+    def is_wsl(self):
+        with guard_platform_info:
+            # Check if its already verified as WSL system or not.
+            if not self.wsl_verified:
+                try:
+                    # Open /proc/version file
+                    with open("/proc/version", "r") as version_file:
+                        # Read the content
+                        version_info = version_file.readline()
+                        version_info = version_info.lower()
+                        self.wsl_verified = True
+
+                        # Check if "microsoft" is present in the version information
+                        if "microsoft" in version_info:
+                            self.is_wsl_system = True
+                except Exception as e:
+                    print(f"ERROR: Opening /proc/version failed: {e}")
+
+        return self.is_wsl_system
+    
+    def is_integrated_gpu(self):
+        #Using cuda apis to identify whether integrated/discreet
+        #This is required to distinguish Tegra and ARM_SBSA devices
+        with guard_platform_info:
+            #Cuda initialize
+            if not self.is_integrated_gpu_verified:
+                cuda_init_result, = cuda.cuInit(0)
+                if  cuda_init_result == cuda.CUresult.CUDA_SUCCESS:
+                    #Get cuda devices count
+                    device_count_result, num_devices = cuda.cuDeviceGetCount()
+                    if device_count_result == cuda.CUresult.CUDA_SUCCESS:
+                        #If atleast one device is found, we can use the property from
+                        #the first device
+                        if num_devices >= 1:
+                            #Get properties from first device
+                            property_result, properties = cudart.cudaGetDeviceProperties(0)
+                            if property_result == cuda.CUresult.CUDA_SUCCESS:
+                                print("Is it Integrated GPU? :", properties.integrated)
+                                self.is_integrated_gpu_system = properties.integrated
+                                self.is_integrated_gpu_verified = True
+                            else:
+                                print("ERROR: Getting cuda device property failed: {}".format(property_result))
+                        else:
+                            print("ERROR: No cuda devices found to check whether iGPU/dGPU")
+                    else:
+                        print("ERROR: Getting cuda device count failed: {}".format(device_count_result))
+                else:
+                    print("ERROR: Cuda init failed: {}".format(cuda_init_result))
+
+        return self.is_integrated_gpu_system
+
+    def is_platform_aarch64(self):
+        #Check if platform is aarch64 using uname
+        if not self.is_aarch64_verified:
+            if platform.uname()[4] == 'aarch64':
+                self.is_aarch64_platform =  True
+            self.is_aarch64_verified = True
+        return self.is_aarch64_platform
+
+sys.path.append('/opt/nvidia/deepstream/deepstream/lib')

apps/common/platform_info.py

@@ -16,7 +16,7 @@
 ################################################################################
 
 Prequisites:
-- DeepStreamSDK 6.4
+- DeepStreamSDK 7.0
 - Python 3.10
 - Gst-python
 

apps/deepstream-custom-binding-test/README

@@ -191,7 +191,7 @@ def main(args):
     source.link(h264parser)
     h264parser.link(decoder)
 
-    sinkpad = streammux.get_request_pad("sink_0")
+    sinkpad = streammux.request_pad_simple("sink_0")
     if not sinkpad:
         Gst.error(" Unable to get the sink pad of streammux")
 

apps/deepstream-custom-binding-test/deepstream_custom_binding_test.py

@@ -16,7 +16,7 @@
 ################################################################################
 
 Prerequisites:
-- DeepStreamSDK 6.4
+- DeepStreamSDK 7.0
 - Python 3.10
 - Gst-python
 

apps/deepstream-demux-multi-in-multi-out/README

@@ -32,7 +32,7 @@
 import os
 import math
 import platform
-from common.is_aarch_64 import is_aarch64
+from common.platform_info import PlatformInfo
 from common.bus_call import bus_call
 from common.FPS import PERF_DATA
 
@@ -265,6 +265,7 @@ def main(args, requested_pgie=None, config=None, disable_probe=False):
     global perf_data
     perf_data = PERF_DATA(number_sources)
 
+    platform_info = PlatformInfo()
     # Standard GStreamer initialization
     Gst.init(None)
 
@@ -294,7 +295,7 @@ def main(args, requested_pgie=None, config=None, disable_probe=False):
             sys.stderr.write("Unable to create source bin \n")
         pipeline.add(source_bin)
         padname = "sink_%u" % i
-        sinkpad = streammux.get_request_pad(padname)
+        sinkpad = streammux.request_pad_simple(padname)
         if not sinkpad:
             sys.stderr.write("Unable to create sink pad bin \n")
         srcpad = source_bin.get_static_pad("src")
@@ -347,14 +348,18 @@ def main(args, requested_pgie=None, config=None, disable_probe=False):
     for i in range(number_sources):
         # pipeline nvstreamdemux -> queue -> nvvidconv -> nvosd -> (if Jetson) nvegltransform -> nveglgl
         # Creating EGLsink
-        if is_aarch64():
+        if platform_info.is_integrated_gpu():
             print("Creating nv3dsink \n")
             sink = make_element("nv3dsink", i)
             if not sink:
                 sys.stderr.write(" Unable to create nv3dsink \n")
         else:
-            print("Creating EGLSink \n")
-            sink = make_element("nveglglessink", i)
+            if platform_info.is_platform_aarch64():
+                print("Creating nv3dsink \n")
+                sink = make_element("nv3dsink", i)
+            else:
+                print("Creating EGLSink \n")
+                sink = make_element("nveglglessink", i)
             if not sink:
                 sys.stderr.write(" Unable to create egl sink \n")
         pipeline.add(sink)
@@ -375,7 +380,7 @@ def main(args, requested_pgie=None, config=None, disable_probe=False):
 
         # connect nvstreamdemux -> queue
         padname = "src_%u" % i
-        demuxsrcpad = nvstreamdemux.get_request_pad(padname)
+        demuxsrcpad = nvstreamdemux.request_pad_simple(padname)
         if not demuxsrcpad:
             sys.stderr.write("Unable to create demux src pad \n")