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make_trafficcamnet_engine_files.py
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make_trafficcamnet_engine_files.py
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################################################################################
# The MIT License
#
# Copyright (c) 2022, Prominence AI, Inc.
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (the "Software"),
# to deal in the Software without restriction, including without limitation
# the rights to use, copy, modify, merge, publish, distribute, sublicense,
# and/or sell copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
# DEALINGS IN THE SOFTWARE.
################################################################################
#!/usr/bin/env python
import sys
import time
from dsl import *
################################################################################
# This script can be used to generate the tensorflow Resnet caffemodel engine
# files using the config files under the installed NVIDIA Samples folder.
#
# Default is set to nano - Swap/update the primary config pathspec for other platforms.
# Test URI used for all sources
uri = '/opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h265.mp4'
# Config file for the Primary GIE
inferConfigFile = \
'/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_infer_primary.txt'
tracker_config_file = \
'/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_tracker_IOU.yml'
# Config files for the Secondary GIEs
sgie1_config_file = \
'/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_infer_secondary_vehiclemake.txt'
sgie2_config_file = \
'/opt/nvidia/deepstream/deepstream/samples/configs/deepstream-app/config_infer_secondary_vehicletypes.txt'
TILER_WIDTH = DSL_1K_HD_WIDTH
TILER_HEIGHT = DSL_1K_HD_HEIGHT
##
# Function to be called on End-of-Stream (EOS) event
##
def eos_event_listener(client_data):
print('Pipeline EOS event')
dsl_main_loop_quit()
def main(args):
# Since we're not using args, we can Let DSL initialize GST on first call
while True:
#
# Create the Pipeline components
# ... starting with eight URI File Sources
retval = dsl_source_uri_new('Camera 1', uri, False, False, 0)
if retval != DSL_RETURN_SUCCESS:
break
dsl_source_uri_new('Camera 2', uri, False, False, 0)
dsl_source_uri_new('Camera 3', uri, False, False, 0)
dsl_source_uri_new('Camera 4', uri, False, False, 0)
dsl_source_uri_new('Camera 5', uri, False, False, 0)
dsl_source_uri_new('Camera 6', uri, False, False, 0)
dsl_source_uri_new('Camera 7', uri, False, False, 0)
dsl_source_uri_new('Camera 8', uri, False, False, 0)
# New Primary GIE using the filespecs above, with interval and Id. Setting the
# model_engine_files parameter to None allows for model generation if not found.
retval = dsl_infer_gie_primary_new('primary-gie',
inferConfigFile, None, interval=10)
if retval != DSL_RETURN_SUCCESS:
break
# New Secondary GIEs using the filespecs above with interval = 0
retval = dsl_infer_gie_secondary_new('vehiclemake-sgie',
sgie1_config_file, None, 'primary-gie', 10)
if retval != DSL_RETURN_SUCCESS:
break
retval = dsl_infer_gie_secondary_new('vehicletype-sgie',
sgie2_config_file, None, 'primary-gie', 10)
if retval != DSL_RETURN_SUCCESS:
break
# New IOU Tracker, setting max width and height of input frame
retval = dsl_tracker_new('tracker', tracker_config_file, 480, 288)
if retval != DSL_RETURN_SUCCESS:
break
# New Tiler, setting width and height, use default cols/rows set by source count
retval = dsl_tiler_new('tiler', TILER_WIDTH, TILER_HEIGHT)
if retval != DSL_RETURN_SUCCESS:
break
# New Fake Sink to terminate the stream.
retval = dsl_sink_fake_new('fake-sink')
if retval != DSL_RETURN_SUCCESS:
break
#----------------------------------------------------------------------------------------------------
# Pipeline assembly
#
# New Pipeline (trunk) with our Sources, Tracker, and Pre-Tiler as last component
# Note: *** change 'iou-tracker' to 'ktl-tracker' to try both. KTL => higher CPU load
retval = dsl_pipeline_new_component_add_many('pipeline',
['Camera 1', 'Camera 2', 'Camera 3', 'Camera 4', 'Camera 5', 'Camera 6',
'Camera 7', 'Camera 8', 'primary-gie', 'tracker', 'vehiclemake-sgie',
'vehicletype-sgie', 'tiler', 'fake-sink', None])
if retval != DSL_RETURN_SUCCESS:
break
retval = dsl_pipeline_eos_listener_add('pipeline', eos_event_listener, None)
if retval != DSL_RETURN_SUCCESS:
break
# Play the pipeline
retval = dsl_pipeline_play('pipeline')
if retval != DSL_RETURN_SUCCESS:
break
# Once the pipeline is playing, the model engine files will have been saved.
# Safe to stop the pipline and quit now.
retval = dsl_pipeline_stop('pipeline')
break
# Print out the final result
print(dsl_return_value_to_string(retval))
dsl_delete_all()
if __name__ == '__main__':
sys.exit(main(sys.argv))