Thanks for the above code!!
Based on the code you provided, I modified code in following places.
- After record_done() signal, Iam just deleting the recorded videos.
- Modified following piece of code
timer_ids = {}
for i, uribin in enumerate(list_for_nvurisrcbin):
timer_id_name = f"timer_id_{i}"
timer_ids[timer_id_name] = GLib.timeout_add_seconds(10, start_sr_function, uribin)
All RTSP are H265 encoded.
But still Iam facing memory leak issues. I am attaching the code and docker stats memory graph below. please have a look and let me know something is wrong.
#!/usr/bin/env python3
################################################################################
# SPDX-FileCopyrightText: Copyright (c) 2019-2023 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
sys.path.append('../')
from pathlib import Path
import gi
import configparser
import argparse
gi.require_version('Gst', '1.0')
from gi.repository import GLib, Gst
from ctypes import *
import time
import sys
import math
import platform
from common.platform_info import PlatformInfo
from common.bus_call import bus_call
from common.FPS import PERF_DATA
import time, threading
import pyds
import os
import ctypes
no_display = False
silent = False
file_loop = False
perf_data = None
MAX_DISPLAY_LEN=64
PGIE_CLASS_ID_VEHICLE = 0
PGIE_CLASS_ID_BICYCLE = 1
PGIE_CLASS_ID_PERSON = 2
PGIE_CLASS_ID_ROADSIGN = 3
MUXER_OUTPUT_WIDTH=1920
MUXER_OUTPUT_HEIGHT=1080
MUXER_BATCH_TIMEOUT_USEC = 33000
TILED_OUTPUT_WIDTH=1280
TILED_OUTPUT_HEIGHT=720
GST_CAPS_FEATURES_NVMM="memory:NVMM"
OSD_PROCESS_MODE= 0
OSD_DISPLAY_TEXT= 1
pgie_classes_str= ["Vehicle", "TwoWheeler", "Person","RoadSign"]
list_for_nvurisrcbin = []
class SRUserContext(ctypes.Structure):
_fields_ = [
("sessionid", ctypes.c_int),
("name", ctypes.c_char * 32)
]
# pgie_src_pad_buffer_probe will extract metadata received on tiler sink pad
# and update params for drawing rectangle, object information etc.
def pgie_src_pad_buffer_probe(pad,info,u_data):
frame_number=0
num_rects=0
got_fps = False
gst_buffer = info.get_buffer()
if not gst_buffer:
print("Unable to get GstBuffer ")
return
# Retrieve batch metadata from the gst_buffer
# Note that pyds.gst_buffer_get_nvds_batch_meta() expects the
# C address of gst_buffer as input, which is obtained with hash(gst_buffer)
batch_meta = pyds.gst_buffer_get_nvds_batch_meta(hash(gst_buffer))
l_frame = batch_meta.frame_meta_list
while l_frame is not None:
try:
# Note that l_frame.data needs a cast to pyds.NvDsFrameMeta
# The casting is done by pyds.NvDsFrameMeta.cast()
# The casting also keeps ownership of the underlying memory
# in the C code, so the Python garbage collector will leave
# it alone.
frame_meta = pyds.NvDsFrameMeta.cast(l_frame.data)
except StopIteration:
break
frame_number=frame_meta.frame_num
l_obj=frame_meta.obj_meta_list
num_rects = frame_meta.num_obj_meta
obj_counter = {
PGIE_CLASS_ID_VEHICLE:0,
PGIE_CLASS_ID_PERSON:0,
PGIE_CLASS_ID_BICYCLE:0,
PGIE_CLASS_ID_ROADSIGN:0
}
while l_obj is not None:
try:
# Casting l_obj.data to pyds.NvDsObjectMeta
obj_meta=pyds.NvDsObjectMeta.cast(l_obj.data)
except StopIteration:
break
obj_counter[obj_meta.class_id] += 1
try:
l_obj=l_obj.next
except StopIteration:
break
if not silent:
print("Frame Number=", frame_number, "Number of Objects=",num_rects,"Vehicle_count=",obj_counter[PGIE_CLASS_ID_VEHICLE],"Person_count=",obj_counter[PGIE_CLASS_ID_PERSON])
# Update frame rate through this probe
stream_index = "stream{0}".format(frame_meta.pad_index)
global perf_data
perf_data.update_fps(stream_index)
try:
l_frame=l_frame.next
except StopIteration:
break
return Gst.PadProbeReturn.OK
def cb_newpad(decodebin, decoder_src_pad,data):
print("In cb_newpad\n")
caps=decoder_src_pad.get_current_caps()
if not caps:
caps = decoder_src_pad.query_caps()
gststruct=caps.get_structure(0)
gstname=gststruct.get_name()
source_bin=data
features=caps.get_features(0)
# Need to check if the pad created by the decodebin is for video and not
# audio.
print("gstname=",gstname)
if(gstname.find("video")!=-1):
# Link the decodebin pad only if decodebin has picked nvidia
# decoder plugin nvdec_*. We do this by checking if the pad caps contain
# NVMM memory features.
print("features=",features)
if features.contains("memory:NVMM"):
# Get the source bin ghost pad
bin_ghost_pad=source_bin.get_static_pad("src")
if not bin_ghost_pad.set_target(decoder_src_pad):
sys.stderr.write("Failed to link decoder src pad to source bin ghost pad\n")
else:
sys.stderr.write(" Error: Decodebin did not pick nvidia decoder plugin.\n")
def decodebin_child_added(child_proxy,Object,name,user_data):
print("Decodebin child added:", name, "\n")
if(name.find("decodebin") != -1):
Object.connect("child-added",decodebin_child_added,user_data)
if "source" in name:
source_element = child_proxy.get_by_name("source")
if source_element.find_property('drop-on-latency') != None:
Object.set_property("drop-on-latency", True)
def create_source_bin(index,uri):
print("Creating source bin")
# Create a source GstBin to abstract this bin's content from the rest of the
# pipeline
bin_name="source-bin-%02d" %index
print(bin_name)
nbin=Gst.Bin.new(bin_name)
if not nbin:
sys.stderr.write(" Unable to create source bin \n")
# Source element for reading from the uri.
# We will use decodebin and let it figure out the container format of the
# stream and the codec and plug the appropriate demux and decode plugins.
if not file_loop:
# use nvurisrcbin to enable file-loop
print("HEY DEB I CAME INSIDE FILE LOOP --------------------------------> I don't know what to do ")
uri_decode_bin=Gst.ElementFactory.make("nvurisrcbin", "uri-decode-bin" + str(index))
# uri_decode_bin.set_property("file-loop", 1)
uri_decode_bin.set_property("cudadec-memtype", 0)
else:
uri_decode_bin=Gst.ElementFactory.make("nvurisrcbin", "uri-decode-bin")
if not uri_decode_bin:
sys.stderr.write(" Unable to create uri decode bin \n")
uri_decode_bin.set_property("smart-record", 2)
dir = f"/opt/nvidia/deepstream/deepstream-7.0/sources/deepstream_python_apps/apps/deepstream-test3/videos"
uri_decode_bin.set_property("smart-rec-dir-path", dir)
uri_decode_bin.set_property("smart-rec-cache", 20) # enable smart record.
uri_decode_bin.set_property("source-id",index)
uri_decode_bin.connect("sr-done", record_done, nbin)
# We set the input uri to the source element
uri_decode_bin.set_property("uri",uri)
global list_for_nvurisrcbin
list_for_nvurisrcbin.append(uri_decode_bin)
# Connect to the "pad-added" signal of the decodebin which generates a
# callback once a new pad for raw data has beed created by the decodebin
uri_decode_bin.connect("pad-added",cb_newpad,nbin)
uri_decode_bin.connect("child-added",decodebin_child_added,nbin)
# We need to create a ghost pad for the source bin which will act as a proxy
# for the video decoder src pad. The ghost pad will not have a target right
# now. Once the decode bin creates the video decoder and generates the
# cb_newpad callback, we will set the ghost pad target to the video decoder
# src pad.
Gst.Bin.add(nbin,uri_decode_bin)
bin_pad=nbin.add_pad(Gst.GhostPad.new_no_target("src",Gst.PadDirection.SRC))
if not bin_pad:
sys.stderr.write(" Failed to add ghost pad in source bin \n")
return None
return nbin
def start_sr_function(element):
sessionid = pyds.get_native_ptr(pyds.alloc_buffer(4))
print(f"sessionid {sessionid}")
sr_user_context_size = ctypes.sizeof(SRUserContext)
sr_user_context_buf = pyds.get_native_ptr(pyds.alloc_buffer(sr_user_context_size))
sr_user_context = pyds.SRUserContext.cast(sr_user_context_buf)
sr_user_context.sessionid = 42
sr_user_context.name = "sr-demo " + element.get_name()
print(f"sr_user_context_buf {sr_user_context_buf} {element.get_name()}")
element.emit('start-sr', sessionid, 5, 5, sr_user_context_buf)
pyds.free_gbuffer(sessionid)
print('******start sr*****')
return True
def record_done(nvurisrcbin, recordingInfo, user_ctx, user_data):
print('******sr done*****')
sr = pyds.SRUserContext.cast(hash(user_ctx))
print(f"session id {sr.sessionid} -- name {sr.name}")
pyds.free_buffer(hash(user_ctx))
try:
latest_mp4=[f for f in os.listdir("/opt/nvidia/deepstream/deepstream-7.0/sources/deepstream_python_apps/apps/deepstream-test3/videos") if f.endswith(".mp4") and f.startswith("Smart_Record")]
directory = f"/opt/nvidia/deepstream/deepstream-7.0/sources/deepstream_python_apps/apps/deepstream-test3/videos"
#latest_mp4.sort(key=lambda x: os.path.getctime(x))
if not os.path.exists(directory):
print(f"Directory {directory} does not exist.")
else:
if not latest_mp4:
print("No .mp4 file found.....")
else:
for file in latest_mp4:
file_path = os.path.join(directory, file)
try:
os.remove(file_path)
print(f"Deleted file: {file_path}")
except OSError as e:
print(f"Error deleting file {file_path}: {e}")
except:
print("CANTTTTTTTTTTTTTTTTTTTTTTTTTTTTT deleteeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee")
def main(args, requested_pgie=None, config=None, disable_probe=False):
global perf_data
perf_data = PERF_DATA(len(args))
number_sources=len(args)
platform_info = PlatformInfo()
# Standard GStreamer initialization
Gst.init(None)
# Create gstreamer elements */
# Create Pipeline element that will form a connection of other elements
print("Creating Pipeline \n ")
pipeline = Gst.Pipeline()
is_live = False
if not pipeline:
sys.stderr.write(" Unable to create Pipeline \n")
print("Creating streamux \n ")
# Create nvstreammux instance to form batches from one or more sources.
streammux = Gst.ElementFactory.make("nvstreammux", "Stream-muxer")
if not streammux:
sys.stderr.write(" Unable to create NvStreamMux \n")
pipeline.add(streammux)
for i in range(number_sources):
print("Creating source_bin ",i," \n ")
uri_name=args[i]
if uri_name.find("rtsp://") == 0 :
is_live = True
source_bin=create_source_bin(i, uri_name)
if not source_bin:
sys.stderr.write("Unable to create source bin \n")
pipeline.add(source_bin)
padname="sink_%u" %i
sinkpad= streammux.get_request_pad(padname)
if not sinkpad:
sys.stderr.write("Unable to create sink pad bin \n")
srcpad=source_bin.get_static_pad("src")
if not srcpad:
sys.stderr.write("Unable to create src pad bin \n")
srcpad.link(sinkpad)
queue1=Gst.ElementFactory.make("queue","queue1")
queue2=Gst.ElementFactory.make("queue","queue2")
queue3=Gst.ElementFactory.make("queue","queue3")
queue4=Gst.ElementFactory.make("queue","queue4")
queue5=Gst.ElementFactory.make("queue","queue5")
pipeline.add(queue1)
pipeline.add(queue2)
pipeline.add(queue3)
pipeline.add(queue4)
pipeline.add(queue5)
nvdslogger = None
print("Creating Pgie \n ")
if requested_pgie != None and (requested_pgie == 'nvinferserver' or requested_pgie == 'nvinferserver-grpc') :
pgie = Gst.ElementFactory.make("nvinferserver", "primary-inference")
elif requested_pgie != None and requested_pgie == 'nvinfer':
pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
else:
pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
if not pgie:
sys.stderr.write(" Unable to create pgie : %s\n" % requested_pgie)
if disable_probe:
# Use nvdslogger for perf measurement instead of probe function
print ("Creating nvdslogger \n")
nvdslogger = Gst.ElementFactory.make("nvdslogger", "nvdslogger")
print("Creating tiler \n ")
tiler=Gst.ElementFactory.make("nvmultistreamtiler", "nvtiler")
if not tiler:
sys.stderr.write(" Unable to create tiler \n")
print("Creating nvvidconv \n ")
nvvidconv = Gst.ElementFactory.make("nvvideoconvert", "convertor")
if not nvvidconv:
sys.stderr.write(" Unable to create nvvidconv \n")
print("Creating nvosd \n ")
nvosd = Gst.ElementFactory.make("nvdsosd", "onscreendisplay")
if not nvosd:
sys.stderr.write(" Unable to create nvosd \n")
nvosd.set_property('process-mode',OSD_PROCESS_MODE)
nvosd.set_property('display-text',OSD_DISPLAY_TEXT)
if file_loop:
if platform_info.is_integrated_gpu():
# Set nvbuf-memory-type=4 for aarch64 for file-loop (nvurisrcbin case)
streammux.set_property('nvbuf-memory-type', 4)
else:
# Set nvbuf-memory-type=2 for x86 for file-loop (nvurisrcbin case)
streammux.set_property('nvbuf-memory-type', 2)
if no_display:
print("Creating Fakesink \n")
sink = Gst.ElementFactory.make("fakesink", "fakesink")
sink.set_property('enable-last-sample', 0)
sink.set_property('sync', 0)
else:
if platform_info.is_integrated_gpu():
print("Creating nv3dsink \n")
sink = Gst.ElementFactory.make("nv3dsink", "nv3d-sink")
if not sink:
sys.stderr.write(" Unable to create nv3dsink \n")
else:
print("Creating EGLSink \n")
sink = Gst.ElementFactory.make("nveglglessink", "nvvideo-renderer")
if not sink:
sys.stderr.write(" Unable to create egl sink \n")
if not sink:
sys.stderr.write(" Unable to create sink element \n")
if is_live:
print("At least one of the sources is live")
streammux.set_property('live-source', 1)
streammux.set_property('width', 1920)
streammux.set_property('height', 1080)
streammux.set_property('batch-size', number_sources)
streammux.set_property('batched-push-timeout', MUXER_BATCH_TIMEOUT_USEC)
if requested_pgie == "nvinferserver" and config != None:
pgie.set_property('config-file-path', config)
elif requested_pgie == "nvinferserver-grpc" and config != None:
pgie.set_property('config-file-path', config)
elif requested_pgie == "nvinfer" and config != None:
pgie.set_property('config-file-path', config)
else:
pgie.set_property('config-file-path', "dstest3_pgie_config.txt")
pgie_batch_size=pgie.get_property("batch-size")
if(pgie_batch_size != number_sources):
print("WARNING: Overriding infer-config batch-size",pgie_batch_size," with number of sources ", number_sources," \n")
pgie.set_property("batch-size",number_sources)
tiler_rows=int(math.sqrt(number_sources))
tiler_columns=int(math.ceil((1.0*number_sources)/tiler_rows))
tiler.set_property("rows",tiler_rows)
tiler.set_property("columns",tiler_columns)
tiler.set_property("width", TILED_OUTPUT_WIDTH)
tiler.set_property("height", TILED_OUTPUT_HEIGHT)
sink.set_property("qos",0)
print("Adding elements to Pipeline \n")
pipeline.add(pgie)
if nvdslogger:
pipeline.add(nvdslogger)
pipeline.add(tiler)
pipeline.add(nvvidconv)
pipeline.add(nvosd)
pipeline.add(sink)
print("Linking elements in the Pipeline \n")
streammux.link(queue1)
queue1.link(pgie)
pgie.link(queue2)
if nvdslogger:
queue2.link(nvdslogger)
nvdslogger.link(tiler)
else:
queue2.link(tiler)
tiler.link(queue3)
queue3.link(nvvidconv)
nvvidconv.link(queue4)
queue4.link(nvosd)
nvosd.link(queue5)
queue5.link(sink)
# create an event loop and feed gstreamer bus mesages to it
loop = GLib.MainLoop()
bus = pipeline.get_bus()
bus.add_signal_watch()
bus.connect ("message", bus_call, loop)
pgie_src_pad=pgie.get_static_pad("src")
if not pgie_src_pad:
sys.stderr.write(" Unable to get src pad \n")
else:
if not disable_probe:
pgie_src_pad.add_probe(Gst.PadProbeType.BUFFER, pgie_src_pad_buffer_probe, 0)
# perf callback function to print fps every 5 sec
GLib.timeout_add(5000, perf_data.perf_print_callback)
# List the sources
print("Now playing...")
for i, source in enumerate(args):
print(i, ": ", source)
print("Starting pipeline \n")
# start play back and listed to events
pipeline.set_state(Gst.State.PLAYING)
global list_for_nvurisrcbin
timer_ids = {}
for i, uribin in enumerate(list_for_nvurisrcbin):
timer_id_name = f"timer_id_{i}"
timer_ids[timer_id_name] = GLib.timeout_add_seconds(10, start_sr_function, uribin)
try:
loop.run()
except:
pass
# cleanup
print("Exiting app\n")
pipeline.set_state(Gst.State.NULL)
def parse_args():
parser = argparse.ArgumentParser(prog="deepstream_test_3",
description="deepstream-test3 multi stream, multi model inference reference app")
parser.add_argument(
"-i",
"--input",
help="Path to input streams",
nargs="+",
metavar="URIs",
default=["a"],
required=True,
)
parser.add_argument(
"-c",
"--configfile",
metavar="config_location.txt",
default=None,
help="Choose the config-file to be used with specified pgie",
)
parser.add_argument(
"-g",
"--pgie",
default=None,
help="Choose Primary GPU Inference Engine",
choices=["nvinfer", "nvinferserver", "nvinferserver-grpc"],
)
parser.add_argument(
"--no-display",
action="store_true",
default=True,
dest='no_display',
help="Disable display of video output",
)
parser.add_argument(
"--file-loop",
action="store_true",
default=False,
dest='file_loop',
help="Loop the input file sources after EOS",
)
parser.add_argument(
"--disable-probe",
action="store_true",
default=False,
dest='disable_probe',
help="Disable the probe function and use nvdslogger for FPS",
)
parser.add_argument(
"-s",
"--silent",
action="store_true",
default=False,
dest='silent',
help="Disable verbose output",
)
# Check input arguments
if len(sys.argv) == 1:
parser.print_help(sys.stderr)
sys.exit(1)
args = parser.parse_args()
stream_paths = args.input
pgie = args.pgie
config = args.configfile
disable_probe = args.disable_probe
global no_display
global silent
global file_loop
# no_display = args.no_display
no_display = True
# silent = args.silent
silent = True
# file_loop = args.file_loop
file_loop = True
if config and not pgie or pgie and not config:
sys.stderr.write ("\nEither pgie or configfile is missing. Please specify both! Exiting...\n\n\n\n")
parser.print_help()
sys.exit(1)
if config:
config_path = Path(config)
if not config_path.is_file():
sys.stderr.write ("Specified config-file: %s doesn't exist. Exiting...\n\n" % config)
sys.exit(1)
print(vars(args))
return stream_paths, pgie, config, disable_probe
if __name__ == '__main__':
stream_paths, pgie, config, disable_probe = parse_args()
sys.exit(main(stream_paths, pgie, config, disable_probe))
Following is the command I used to run above code.
python3 smart_record.py -i rtsp://media/xxxxx rtsp://media/xxxxx rtsp://media/xxxxx rtsp://media/xxxxx rtsp://media/xxxxx rtsp://media/xxxxx rtsp://media/xxxxx rtsp://media/xxxxx rtsp://media/xxxxx -c /opt/nvidia/deepstream/deepstream-7.0/sources/deepstream_python_apps/apps/deepstream-test3/dstest3_pgie_config.txt -g nvinfer
In the below graph, for sometime it is good and then in the middle it is throwing below error and I am thinking because of the below error, sudden increment in leak.
libv4l2: error getting capabilities: Invalid argument
Failed to query video capabilities: Invalid argument
./log_docker_stats.sh
TegraV4L2_Open for ENCODER failed: Success
libv4l2: error getting capabilities: Invalid argument
Failed to query video capabilities: Invalid argument
libv4l2: error getting capabilities: Invalid argument
Following is the graph
@junshengy
Thanks
