Optimizer#

DLS Optimizer is a tool for helping users discover more optimal versions of the pipelines they run on DL Streamer. It will explore different modifications to your pipeline that are known to increase performance and measure them. As a result, you can expect to receive a pipeline that is better suited to your setup.

Optimizations involve modifying inference elements that are part of DL Streamer, as well as searching for pre- and post-processing elements better suited for the pipeline.

Modification of inference elements currently covers:

Discovering more suitable devices
Adjusting the batching of frames in an element
Adjusting the number of inference requests done simultaneously (nireqs)

Limitations#

Currently the DLS Optimizer focuses mainly on DL Streamer elements, specifically the gvadetect and gvaclassify. The produced pipeline could still have potential for further optimization by transforming other elements.

Multi-stream pipelines (those utilizing the tee element) are also currently not supported.

Prerequisites#

Before using the DLS Optimizer, ensure you have the OpenVINO Python module installed. You can install it by running the following command:

pip install openvino

Using the optimizer as a tool#

Note
This example assumes your working directory is the optimizer directory /opt/intel/dlstreamer/scripts/optimizer

python3 . MODE [OPT] -- PIPELINE

Arguments:
  MODE      The type of optimization that will be performed on the pipeline.
            Possible values are \"fps\" and \"streams\".

            fps - the optimizer will explore possible alternatives
                  for the pipeline, trying to locate versions that
                  have increased performance measured by fps.

            streams - the optimizer will explore possible alternatives
                      for the pipeline, trying to locate a version which
                      can support the most streams at once without
                      crossing a minimum fps threshold.
                      (check \"multistream-fps-limit for more info)

  PIPELINE  A string representing a pipeline in the GStreamer notation
            which the tool will attempt to optimize.

Options:
    --search-duration SEARCH_DURATION   How long should the optimizer search for better pipelines
    --sample-duration SAMPLE_DURATION   How long should every pipeline be sampled for performance
    --multistream-fps-limit LIMIT       Minimum fps limit which streams are not allowed to cross
                                        when optimizing for a multi-stream scenario.
    --log-level LEVEL                   Configure the logging detail level

search-duration default: 300 seconds
Increasing the search duration will increase the chances of discovering more performant pipelines.

sample-duration default: 10 seconds
Increasing the sample duration will improve the stability of the search.

multistream-fps-limit default: 30 fps
Increasing the multi-stream fps limit will improve the performance of each individual stream, but the final result is liable to support less streams overall.

log-level default: INFO
Available log levels are: CRITICAL, FATAL, ERROR, WARN, INFO, DEBUG.

Note
Search duration and sample duration both affect the amount of pipelines that will be explored during the search.
The total amount should be approximately search_duration / sample_duration pipelines.

Example#

 python3 . fps -- urisourcebin buffer-size=4096 uri=https://videos.pexels.com/video-files/1192116/1192116-sd_640_360_30fps.mp4 ! decodebin ! gvadetect model=/home/optimizer/models/public/yolo11s/INT8/yolo11s.xml ! queue ! gvawatermark ! fakesink
[__main__] [    INFO] - GStreamer initialized successfully
[__main__] [    INFO] - GStreamer version: 1.26.6
[__main__] [    INFO] - Detected GPU Device
[__main__] [    INFO] - No NPU Device detected
[__main__] [    INFO] - Sampling for 10 seconds...
FpsCounter(last 1.00sec): total=46.87 fps, number-streams=1, per-stream=46.87 fps
FpsCounter(average 1.00sec): total=46.87 fps, number-streams=1, per-stream=46.87 fps
FpsCounter(last 1.01sec): total=43.70 fps, number-streams=1, per-stream=43.70 fps
FpsCounter(average 2.01sec): total=45.28 fps, number-streams=1, per-stream=45.28 fps

...

FpsCounter(last 1.09sec): total=73.45 fps, number-streams=1, per-stream=73.45 fps
FpsCounter(average 8.70sec): total=73.65 fps, number-streams=1, per-stream=73.65 fps
[__main__] [    INFO] - Best found pipeline: urisourcebin buffer-size=4096 uri=https://videos.pexels.com/video-files/1192116/1192116-sd_640_360_30fps.mp4 !decodebin3!gvadetect model=/home/optimizer/models/public/yolo11s/INT8/yolo11s.xml device=GPU pre-process-backend=va-surface-sharing batch-size=2 nireq=2 ! queue ! gvawatermark ! fakesink with fps: 81.987923.2

In this case the optimizer started with a pipeline that ran at ~45fps, and found a pipeline that ran at ~82fps instead. The specific improvements were:

replacing the decodebin with the decodebin3 element.
configuring the gvadetect element to use GPU for processing
setting the batch-size parameter to 2
setting the nireq parameter to 2

Using the optimizer as a library#

The easiest way of importing the optimizer into your scripts is to include it in your PYTHONPATH environment variable: export PYTHONPATH=/opt/intel/dlstreamer/scripts/optimizer

Targets which are exported in order to facilitate usage inside of scripts:

`preprocess_pipeline(pipeline) -> processed_pipeline`#

pipeline - A string containing a valid DL Streamer pipeline.
processed_pipeline - A string containing the pipeline with all relevant substitutions.

Perform quick search and replace for known combinations of elements with more performant alternatives.

`DLSOptimizer class`#

Initialized without any arguments

optimizer = DLSOptimizer()

Methods#

set_search_duration(duration)

duration - The duration of searching for optimized pipelines in seconds, default 300.

Configures the search duration used in optimization sessions.

optimizer = DLSOptimizer()
optimizer.set_search_duration(600)

set_sample_duration(duration)

duration - The duration of sampling each candidate pipeline in seconds, default 10.

Configures the sample duration used in optimization sessions.

optimizer = DLSOptimizer()
optimizer.set_sample_duration(15)

set_mutlistream_fps_limit(limit)

limit - The minimum fps limit allowed for individual streams when optimizing for amount of streams, default 30.

Configures the minimum fps limit that streams are not allowed to fall below when optimizing for a multi-stream scenario.

optimizer = DLSOptimizer()
optimizer.set_multistream_fps_limit(45)

optimize_for_fps(pipeline) -> optimized_pipeline, fps

pipeline - A string containing a valid DL Streamer pipeline.
optimized_pipeline - A string containing the best performing pipeline that has been found during the search.
fps - The measured fps of the best perfmorming pipeline.

Runs a series of optimization steps on the pipeline searching for version with better performance measured by fps.

pipeline = "urisourcebin buffer-size=4096 uri=https://videos.pexels.com/video-files/1192116/1192116-sd_640_360_30fps.mp4 ! decodebin ! gvadetect model=/home/optimizer/models/public/yolo11s/INT8/yolo11s.xml ! queue ! gvawatermark ! fakesink"
optimizer = DLSOptimizer()
optimizer.optimize_for_fps(pipeline)

optimize_for_streams(pipeline) -> optimized_pipeline, fps, streams

pipeline - A string containing a valid DL Streamer pipeline.
optimized_pipeline - A string containing the best performing pipeline that has been found during the search.
fps - The measured fps of the best perfmorming pipeline.
streams - The number of streams capable of running above the fps limit with the optimized pipeline.

Searching for a version of the input pipeline which can support the highest number of concurrent streams.

pipeline = "urisourcebin buffer-size=4096 uri=https://videos.pexels.com/video-files/1192116/1192116-sd_640_360_30fps.mp4 ! decodebin ! gvadetect model=/home/optimizer/models/public/yolo11s/INT8/yolo11s.xml ! queue ! gvawatermark ! fakesink"
optimizer = DLSOptimizer()
optimizer.optimize_for_streams(pipeline)

Runs a series of optimization steps on the pipeline searching for a better performing versions.

Example#

from optimizer import get_optimized_pipeline

pipeline = "urisourcebin buffer-size=4096 uri=https://videos.pexels.com/video-files/1192116/1192116-sd_640_360_30fps.mp4 ! decodebin ! gvadetect model=/home/optimizer/models/public/yolo11s/INT8/yolo11s.xml ! queue ! gvawatermark ! fakesink"

optimizer = DLSOptimizer()
optimizer.set_search_duration(600)
optimizer.set_sample_duration(15)
optimized_pipeline, fps = optimizer.optimize_for_fps(pipeline)
print("Best discovered pipeline: " + optimized_pipeline)
print("Measured fps: " + fps)

Controling the measurement#

The point at which performance is being measured can be controlled by pre-emptively inserting a gvafpscounter element into your pipeline definition. For pipelines which lack such an element, the measurement is done after the last inference element supported by the optimizer tool.

Optimizer#

Limitations#

Prerequisites#

Using the optimizer as a tool#

Example#

Using the optimizer as a library#

preprocess_pipeline(pipeline) -> processed_pipeline#

DLSOptimizer class#

Methods#

Example#

Controling the measurement#

This Page

`preprocess_pipeline(pipeline) -> processed_pipeline`#

`DLSOptimizer class`#