Please provide complete information as applicable to your setup.
• Hardware Platform (Jetson)
**• DeepStream Version5.1
• JetPack Version (4.5)
**• TensorRT Version7.x
Hi !
In the python version of the deepstream example (deep stream-test3), I connected an 8-way IP camera (1080p) and used nvoverlaysink,The following is part of my source code:
# Check input arguments
def main(args):
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)
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")
print("Creating nvvidconv1 \n ")
nvvidconv1 = Gst.ElementFactory.make("nvvideoconvert", "convertor1")
if not nvvidconv1:
sys.stderr.write(" Unable to create nvvidconv1 \n")
nvvidconv1.set_property("src-crop","200:200:360:640")
nvvidconv1.set_property("nvbuf-memory-type", 4)
nvvidconv1.set_property("compute-hw", 1)
nvvidconv1.set_property("gpu-id", 0)
print("Creating filter1 \n ")
pipeline.add(nvvidconv1)
pipeline.add(streammux)
for i in range(number_sources):
print("Creating source_bin ",i," \n ")
uri_name=args[i+1]
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)
queue0=Gst.ElementFactory.make("queue","queue0")
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(queue0)
pipeline.add(queue1)
pipeline.add(queue2)
pipeline.add(queue3)
pipeline.add(queue4)
pipeline.add(queue5)
print("Creating Pgie \n ")
pgie = Gst.ElementFactory.make("nvinfer", "primary-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")
nvvidconv.set_property("nvbuf-memory-type", 4)
nvvidconv.set_property("compute-hw", 1)
nvvidconv.set_property("gpu-id", 0)
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)
nvosd.set_property('gpu-id', 0)
nvosd.set_property('process-mode', 2)
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("nvoverlaysink", "nvvideo-renderer")
sink.set_property("qos", 0)
sink.set_property('sync',0)
sink.set_property('overlay-x',200)
sink.set_property('overlay-y',100)
sink.set_property('overlay-w',1440)
sink.set_property('overlay-h',1280)
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', 1920)
streammux.set_property('height', 1080)
streammux.set_property('batch-size', number_sources)
streammux.set_property('batched-push-timeout', 40000)
streammux.set_property('compute-hw', 1)
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",2)
tiler.set_property("columns",4)
tiler.set_property("width", 1440)
tiler.set_property("height", 1280)
tiler.set_property("nvbuf-memory-type", 4)
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(nvvidconv1)
nvvidconv1.link(queue0)
queue0.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)
queue5.link(sink)
else:
nvosd.link(queue5)
queue5.link(sink)
My problems
1)When I access the 8-channel RTSP video stream, the picture cannot be fully displayed.
I connected 8 RTSP data streams, but only three screens were displayed,The nano operates at maximum power.
So, how can I modify the code so that all 8 pictures can be displayed.
2)Will the other five black screens affect reasoning? For example, if a pedestrian appears in the fifth picture, can the model detect it?