This page documents the following examples:
- Pipeline with Source Meter Pad Probe Handler and Component Queue Management
- Using a Simple DSL Player to test an RTSP Source Connection
- Running Inference on all MP4 files in a Folder
8uri_file_pph_meter_performace_reporting.py- cpp example is still to be done
#
# This example demostrates how to use a Source Meter Pad Probe Handler (PPH)
# that will measure the Pipeline's throughput for each Source - while monitoring
# the depth of every component's Queue.
#
# The Meter PPH is added to the sink (input) pad of the Tiler before tha batched
# stream is converted into a single stream as a 2D composite of all Sources.
#
# The "meter_pph_handler" callback added to the Meter PPH will handle writing
# the Avg Session FPS and the Avg Interval FPS measurements to the console.
# #
# The Key-released-handler callback (below) will disable the meter when pausing
# the Pipeline, and # re-enable measurements when the Pipeline is resumed.
#
# Note: Session averages are reset each time the Meter is disabled and
# then re-enabled.
#
# The callback, called once per second as defined during Meter construction,
# is also responsible for polling the components for their queue depths - i.e
# using the "dsl_component_queue_current_level_print_many" service.
#
# Additionally, a Queue Overrun Listener is added to each of the components to
# be notified on the event of a queue-overrun.
#
# https://github.com/prominenceai/deepstream-services-library/blob/master/docs/api-component.md#component-queue-management
#Example of the metrics that are printed every second.
FPS 0 (AVG) FPS 1 (AVG) FPS 2 (AVG) FPS 3 (AVG) FPS 4 (AVG) FPS 5 (AVG) FPS 6 (AVG) FPS 7 (AVG)
30.00 (30.99) 30.00 (30.99) 30.00 (30.99) 30.00 (30.99) 30.00 (30.99) 30.00 (30.99) 30.00 (30.99) 30.00 (30.99)
'current-level-buffers' = 0/200 for component 'uri-source-0'
'current-level-buffers' = 0/200 for component 'uri-source-1'
'current-level-buffers' = 0/200 for component 'uri-source-2'
'current-level-buffers' = 0/200 for component 'uri-source-3'
'current-level-buffers' = 0/200 for component 'uri-source-4'
'current-level-buffers' = 0/200 for component 'uri-source-5'
'current-level-buffers' = 0/200 for component 'uri-source-6'
'current-level-buffers' = 0/200 for component 'uri-source-7'
'current-level-buffers' = 0/200 for component 'primary-gie'
'current-level-buffers' = 0/200 for component 'iou-tracker'
'current-level-buffers' = 3/200 for component 'tiler'
'current-level-buffers' = 3/200 for component 'on-screen-display'
'current-level-buffers' = 3/200 for component 'window-sink'
rtsp_player_to_test_connections.py- cpp example is still to be done
#
# This example can be used to test your RTSP Source connection. It uses a simple
# DSL Player with a single RTSP Source and Window Sink:
#
# There two example camera URI's below. One for AMCREST and one for HIKVISION.
# update one of the URI's with your username and password, or add your own
# URI format as needed.
#
# Ensure that the RTSP Source constructor is using the correct URI.
#
# The example registers handler callback functions to be notified of:
# - key-release events
# - delete-window events
# - RTSP Source change-of-state events
# process_all_mp4_files_in_folder.py- cpp example is still to be done
#
# This simple example demonstrates how to process (infer-on) all .mp4 files
# in a given folder.
#
# The inference Pipeline is built with the following components:
# - URI Source
# - Primary GST Inference Engine (PGIE)
# - IOU Tracker
# - On-Screen Display (OSD)
# - Window Sink
#
# A Custom Pad-Probe-Handler is added to the Sink-Pad of the OSD
# to process the frame and object meta-data for each buffer received
#
# The example registers handler callback functions with the Pipeline for:
# - key-release events
# - delete-window events
# - end-of-stream EOS events
# - Pipeline change-of-state events.
#
# IMPORTANT! it is the end-of-stream (EOS) listener "eos_event_listener"
# that stops the Pipeline on EOS, sets the URI to the next file in
# the list, and starts the Pipeline again.
#