Hi,
I’ve got a Jetson Xavier using jetpack 4.4 with Deepstream 5.0. I have been testing the USB sample app from the python sample applications. It works well with one camera, but my knowledge of Deepstream/Gstreamer isn’t deep enough to modify it to work for multiple cameras. Would anyone be able to tell me how I can do this?
Thanks,
Kassian
Figured it out, hope this helps someone else. Just make sure you change the resolution to be the same as your camera. I’m using a stereo cam which is why its so wide:
#!/usr/bin/env python3
################################################################################
# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#
# 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.
################################################################################
import sys
sys.path.append('../')
import gi
import configparser
gi.require_version('Gst', '1.0')
from gi.repository import GObject, Gst
from gi.repository import GLib
from ctypes import *
import time
import sys
import math
import platform
from common.is_aarch_64 import is_aarch64
from common.bus_call import bus_call
from common.FPS import GETFPS
import pyds
fps_streams={}
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=1344
MUXER_OUTPUT_HEIGHT=376
MUXER_BATCH_TIMEOUT_USEC=4000000
TILED_OUTPUT_WIDTH=1344
TILED_OUTPUT_HEIGHT=376 * 2
GST_CAPS_FEATURES_NVMM="memory:NVMM"
OSD_PROCESS_MODE= 0
OSD_DISPLAY_TEXT= 0
pgie_classes_str= ["Vehicle", "TwoWheeler", "Person","RoadSign"]
# tiler_sink_pad_buffer_probe will extract metadata received on OSD sink pad
# and update params for drawing rectangle, object information etc.
def tiler_src_pad_buffer_probe(pad,info,u_data):
frame_number=0
num_rects=0
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
'''
print("Frame Number is ", frame_meta.frame_num)
print("Source id is ", frame_meta.source_id)
print("Batch id is ", frame_meta.batch_id)
print("Source Frame Width ", frame_meta.source_frame_width)
print("Source Frame Height ", frame_meta.source_frame_height)
print("Num object meta ", frame_meta.num_obj_meta)
'''
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
"""display_meta=pyds.nvds_acquire_display_meta_from_pool(batch_meta)
display_meta.num_labels = 1
py_nvosd_text_params = display_meta.text_params[0]
py_nvosd_text_params.display_text = "Frame Number={} Number of Objects={} Vehicle_count={} Person_count={}".format(frame_number, num_rects, vehicle_count, person)
py_nvosd_text_params.x_offset = 10;
py_nvosd_text_params.y_offset = 12;
py_nvosd_text_params.font_params.font_name = "Serif"
py_nvosd_text_params.font_params.font_size = 10
py_nvosd_text_params.font_params.font_color.red = 1.0
py_nvosd_text_params.font_params.font_color.green = 1.0
py_nvosd_text_params.font_params.font_color.blue = 1.0
py_nvosd_text_params.font_params.font_color.alpha = 1.0
py_nvosd_text_params.set_bg_clr = 1
py_nvosd_text_params.text_bg_clr.red = 0.0
py_nvosd_text_params.text_bg_clr.green = 0.0
py_nvosd_text_params.text_bg_clr.blue = 0.0
py_nvosd_text_params.text_bg_clr.alpha = 1.0
#print("Frame Number=", frame_number, "Number of Objects=",num_rects,"Vehicle_count=",vehicle_count,"Person_count=",person)
pyds.nvds_add_display_meta_to_frame(frame_meta, display_meta)"""
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])
# Get frame rate through this probe
fps_streams["stream{0}".format(frame_meta.pad_index)].get_fps()
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()
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(is_aarch64() and name.find("nvv4l2decoder") != -1):
print("Seting bufapi_version\n")
Object.set_property("bufapi-version",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.
# uri_decode_bin=Gst.ElementFactory.make("uridecodebin", "uri-decode-bin")
# if not uri_decode_bin:
# sys.stderr.write(" Unable to create uri decode bin \n")
# # We set the input uri to the source element
# uri_decode_bin.set_property("uri",uri)
print("Creating Source \n ")
source = Gst.ElementFactory.make("v4l2src", "usb-cam-source")
if not source:
sys.stderr.write(" Unable to create source \n")
caps_v4l2src = Gst.ElementFactory.make("capsfilter", "v4l2src_caps")
if not caps_v4l2src:
sys.stderr.write("Could not create caps_v4l2src")
# videoconvert to make sure a superset of raw formats are supported
vidconvsrc = Gst.ElementFactory.make("videoconvert", "convertor_src1")
if not vidconvsrc:
sys.stderr.write(" Unable to create videoconvert \n")
# nvvideoconvert to convert incoming raw buffers to NVMM Mem (NvBufSurface API)
nvvidconvsrc = Gst.ElementFactory.make("nvvideoconvert", "convertor_src2")
if not nvvidconvsrc:
sys.stderr.write(" Unable to create Nvvideoconvert \n")
caps_vidconvsrc = Gst.ElementFactory.make("capsfilter", "nvmm_caps")
if not caps_vidconvsrc:
sys.stderr.write(" Unable to create capsfilter \n")
caps_v4l2src.set_property('caps', Gst.Caps.from_string("video/x-raw, framerate=15/1"))
caps_vidconvsrc.set_property('caps', Gst.Caps.from_string("video/x-raw(memory:NVMM)"))
source.set_property('device', uri)
nbin.add(source)
nbin.add(caps_v4l2src)
nbin.add(vidconvsrc)
nbin.add(nvvidconvsrc)
nbin.add(caps_vidconvsrc)
source.link(caps_v4l2src)
caps_v4l2src.link(vidconvsrc)
vidconvsrc.link(nvvidconvsrc)
nvvidconvsrc.link(caps_vidconvsrc)
# 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)
srcpad = caps_vidconvsrc.get_static_pad("src")
bin_pad=nbin.add_pad(Gst.GhostPad.new("src",srcpad))
if not bin_pad:
sys.stderr.write(" Failed to add ghost pad in source bin \n")
return None
return nbin
#For reference here is the code for setting up the pipelines and the linking for the app:
def main(args):
# Check input arguments
if len(args) < 2:
sys.stderr.write("usage: %s <uri1> [uri2] ... [uriN]\n" % args[0])
sys.exit(1)
for i in range(0,len(args)-1):
fps_streams["stream{0}".format(i)]=GETFPS(i)
print(GETFPS(i))
number_sources=len(args)-1
# Standard GStreamer initialization
GObject.threads_init()
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 ")
usb_cam=args[i+1]
# if uri_name.find("rtsp://") == 0 :
is_live = True
source_bin=create_source_bin(i, usb_cam)
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)
print("Creating Pgie \n ")
pgie = Gst.ElementFactory.make("nvinfer", "p376rimary-inference")
if not pgie:
sys.stderr.write(" Unable to create pgie \n")
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(is_aarch64()):
print("Creating transform \n ")
transform=Gst.ElementFactory.make("nvegltransform", "nvegl-transform")
if not transform:
sys.stderr.write(" Unable to create transform \n")
print("Creating EGLSink \n")
sink = Gst.ElementFactory.make("nveglglessink", "nvvideo-renderer")
#sink = Gst.ElementFactory.make("nvoverlaysink", "nvvideo-renderer")
sink.set_property('sync', 0)
if not sink:
sys.stderr.write(" Unable to create egl sink \n")
if is_live:
print("Atleast one of the sources is live")
streammux.set_property('live-source', 1)
streammux.set_property('width', 1344)
streammux.set_property('height', 376)
streammux.set_property('batch-size', number_sources)
streammux.set_property('batched-push-timeout', 4000000)
pgie.set_property('config-file-path', "config_infer_primary_yoloV3.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_rows=2
#tiler_columns=int(math.ceil((1.0*number_sources)/tiler_rows))
tiler_columns=1
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)
pipeline.add(tiler)
pipeline.add(nvvidconv)
pipeline.add(nvosd)
if is_aarch64():
pipeline.add(transform)
pipeline.add(sink)
print("Linking elements in the Pipeline \n")
streammux.link(queue1)
queue1.link(pgie)
pgie.link(queue2)
queue2.link(tiler)
tiler.link(queue3)
queue3.link(nvvidconv)
nvvidconv.link(queue4)
queue4.link(nvosd)
if is_aarch64():
nvosd.link(queue5)
queue5.link(transform)
transform.link(sink)
else:
nvosd.link(queue5)
queue5.link(sink)
# create an event loop and feed gstreamer bus mesages to it
loop = GObject.MainLoop()
bus = pipeline.get_bus()
bus.add_signal_watch()
bus.connect ("message", bus_call, loop)
tiler_src_pad=pgie.get_static_pad("src")
if not tiler_src_pad:
sys.stderr.write(" Unable to get src pad \n")
else:
tiler_src_pad.add_probe(Gst.PadProbeType.BUFFER, tiler_src_pad_buffer_probe, 0)
# List the sources
print("Now playing...")
for i, source in enumerate(args):
if (i != 0):
print(i, ": ", source)
print("Starting pipeline \n")
# start play back and listed to events
pipeline.set_state(Gst.State.PLAYING)
try:
loop.run()
except:
pass
# cleanup
print("Exiting app\n")
pipeline.set_state(Gst.State.NULL)
if __name__ == '__main__':
sys.exit(main(sys.argv))
Many thanks for sharing. At least a good start for new adventures. I was wondering, why you are setting the batch_size to number of devices? IMHO this slows down the frame rate a bit.
EDIT: Ah, stereo cam… Yes, makes sense then
so does it take just the videofeed or also does inference?
It does also inference.
do you know how to stop the inference?
No sorry, I just CTRL_C at console level…
But just a guess: Close the input
no, i didnt mean that, nvm thanks