Setup:
• Jetson AGX Xavier
• DeepStream 5.0
• JetPack Version 4.4
Hi,
I’ve been trying to combine the DS python multistream example together with open CV and PyQt5. I’ve also added the tracker from a different example together with its config file into the pipeline.
So without the part where I save the image and send it to the appropriate QLabel in my UI, everything runs smoothly. But as soon as I add in a cv.resize and set the label as an image, a delay is present, which gradually gets worse and worse. My goal is to send frames from 3 different streams into 3 different QLabels but the resulting delay is much worse so I need to at least have 1 stream working properly.
This is the part where I grab the image and send it to the UI inside the tiler_sink_pad function:
def display_frame(self, flag, buff, b_id, obj_meta):
rgbImage=pyds.get_nvds_buf_surface(hash(buff),b_id)
#convert python array into numy array format.
frame_image=np.array(rgbImage,copy=True,order=‘C’)
if flag:
frame_image=self.draw_bounding_boxes(frame_image,obj_meta,obj_meta.confidence)
frame_image1 = cv2.resize(frame_image, (self.dim1), interpolation = cv2.INTER_AREA)
frame_image2 = cv2.resize(frame_image, (self.dim2), interpolation = cv2.INTER_AREA)
frame_image3 = cv2.resize(frame_image, (self.dim3), interpolation = cv2.INTER_AREA)
self.p1=qimage2ndarray.array2qimage(frame_image1)
self.p2=qimage2ndarray.array2qimage(frame_image2)
self.p3=qimage2ndarray.array2qimage(frame_image3)
self.label.setPixmap(QPixmap.fromImage(self.p1))
self.labels1.setPixmap(QPixmap.fromImage(self.p2))
self.labels2.setPixmap(QPixmap.fromImage(self.p3))
I’ve tried changing the interval in the config file to 30, skipping frames, setting power usage to max + jetson clocks, but to no avail.
Any information as to why this is happening and possible solutions are welcome. I thought of resetting the pipeline every 200 frames but setting the gst.state to “Null” or “Pause” and then “Playing” again just crashes the whole app.
The entire app(without our proprietary code) :
fps_streams={}
frame_count={}
saved_count={}
global PGIE_CLASS_ID_VEHICLE
PGIE_CLASS_ID_VEHICLE=0
global PGIE_CLASS_ID_PERSON
PGIE_CLASS_ID_PERSON=2
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=4000000
TILED_OUTPUT_WIDTH=1920
TILED_OUTPUT_HEIGHT=1080
GST_CAPS_FEATURES_NVMM=“memory:NVMM”
pgie_classes_str= [“Vehicle”, “TwoWheeler”, “Person”,“RoadSign”]
class Deep(QMainWindow):
def __init__(self):
self.main()
# tiler_sink_pad_buffer_probe will extract metadata received on tiler src pad
# and update params for drawing rectangle, object information etc.
def tiler_sink_pad_buffer_probe(self,pad,info,u_data):
# Get dashboard weather data
start = timer()
current = timer()
real = current - self.timed
self.set_dash(real)
'''
# Advance progress bar
'''
j=1
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("stopped")
frame_number=frame_meta.frame_num
l_obj=frame_meta.obj_meta_list
num_rects = frame_meta.num_obj_meta
is_first_obj = True
save_image = False
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:
print("stopped")
#break
obj_counter[obj_meta.class_id] += 1
# Periodically check for objects with borderline confidence value that may be false positive detections.
# If such detections are found, annoate the frame with bboxes and confidence value.
# Save the annotated frame to file.
if((saved_count["stream_"+str(frame_meta.pad_index)]%30==0) and (obj_meta.confidence>=0.3 and obj_meta.confidence<0.31)):
if is_first_obj:
is_first_obj = False
# Getting Image data using nvbufsurface
# the input should be address of buffer and batch_id
#convert python array into numy array format.
frame_image=np.array(n_frame,copy=True,order='C')
#covert the array into cv2 default color format
frame_image=cv2.cvtColor(frame_image,cv2.COLOR_RGBA2BGRA)
save_image = True
j=0
self.display_frame(1, gst_buffer, frame_meta.batch_id,obj_meta)
try:
l_obj=l_obj.next
except StopIteration:
break
else:
self.display_frame(0, gst_buffer, frame_meta.batch_id,0)
# Get frame rate through this probe
fps_streams["stream{0}".format(frame_meta.pad_index)].get_fps()
saved_count["stream_"+str(frame_meta.pad_index)]+=1
try:
l_frame=l_frame.next
except StopIteration:
break
self.frame_skip+=1
return Gst.PadProbeReturn.OK
def draw_bounding_boxes(self,image,obj_meta,confidence):
confidence='{0:.2f}'.format(confidence)
rect_params=obj_meta.rect_params
top=int(rect_params.top)
left=int(rect_params.left)
width=int(rect_params.width)
height=int(rect_params.height)
obj_name=pgie_classes_str[obj_meta.class_id]
image=cv2.rectangle(image,(left,top),(left+width,top+height),(0,0,255,0),2)
# Note that on some systems cv2.putText erroneously draws horizontal lines across the image
image=cv2.putText(image,',ID = '+str(obj_meta.object_id),(left-10,top-10),cv2.FONT_HERSHEY_SIMPLEX,0.5,(0,0,255,0),2)
return image
def display_frame(self, flag, buff, b_id, obj_meta):
rgbImage=pyds.get_nvds_buf_surface(hash(buff),b_id)
#convert python array into numy array format.
frame_image=np.array(rgbImage,copy=True,order='C')
if flag:
frame_image=self.draw_bounding_boxes(frame_image,obj_meta,obj_meta.confidence)
frame_image1 = cv2.resize(frame_image, (self.dim1), interpolation = cv2.INTER_AREA)
frame_image2 = cv2.resize(frame_image, (self.dim2), interpolation = cv2.INTER_AREA)
frame_image3 = cv2.resize(frame_image, (self.dim3), interpolation = cv2.INTER_AREA)
self.p1=qimage2ndarray.array2qimage(frame_image1)
self.p2=qimage2ndarray.array2qimage(frame_image2)
self.p3=qimage2ndarray.array2qimage(frame_image3)
self.label.setPixmap(QPixmap.fromImage(self.p1))
self.labels1.setPixmap(QPixmap.fromImage(self.p2))
self.labels2.setPixmap(QPixmap.fromImage(self.p3))
def cb_newpad(self,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.
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.
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(self,child_proxy,Object,name,user_data):
print("Decodebin child added:", name, "\n")
if(name.find("decodebin") != -1):
Object.connect("child-added",self.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(self,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)
# 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",self.cb_newpad,nbin)
uri_decode_bin.connect("child-added",self.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 main(self):
# Check input arguments
args = ['deepstream_imagedata-multistream.py',"rtsp://gadiadmin:gadiadmin@10.0.0.7:554/stream1", 'frames22']
#if len(args) < 2:
# sys.stderr.write("usage: %s <uri1> [uri2] ... [uriN] <folder to save frames>\n" % args[0])
# sys.exit(1)
for i in range(0,len(args)-2):
fps_streams["stream{0}".format(i)]=GETFPS(i)
number_sources=len(args)-2
#global folder_name
#folder_name=args[-1]
#if path.exists(folder_name):
# sys.stderr.write("The output folder %s already exists. Please remove it first.\n" % folder_name)
# sys.exit(1)
#os.mkdir(folder_name)
#print("Frames will be saved in ",folder_name)
# 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 ")
self.pipeline = Gst.Pipeline()
is_live = False
if not self.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")
self.pipeline.add(streammux)
for i in range(number_sources):
# os.mkdir(folder_name+"/stream_"+str(i))
frame_count["stream_"+str(i)]=0
saved_count["stream_"+str(i)]=0
print("Creating source_bin ",i," \n ")
uri_name=args[i+1]
if uri_name.find("rtsp://") == 0 :
is_live = True
source_bin=self.create_source_bin(i, uri_name)
if not source_bin:
sys.stderr.write("Unable to create source bin \n")
self.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)
print("Creating Pgie \n ")
pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
if not pgie:
sys.stderr.write(" Unable to create pgie \n")
# Tracker
tracker = Gst.ElementFactory.make("nvtracker", "tracker")
if not tracker:
sys.stderr.write(" Unable to create tracker \n")
# Add nvvidconv1 and filter1 to convert the frames to RGBA
# which is easier to work with in Python.
sgie1 = Gst.ElementFactory.make("nvinfer", "secondary1-nvinference-engine")
if not sgie1:
sys.stderr.write(" Unable to make sgie1 \n")
print("Creating nvvidconv1 \n ")
nvvidconv1 = Gst.ElementFactory.make("nvvideoconvert", "convertor1")
if not nvvidconv1:
sys.stderr.write(" Unable to create nvvidconv1 \n")
print("Creating filter1 \n ")
caps1 = Gst.Caps.from_string("video/x-raw(memory:NVMM), format=RGBA")
filter1 = Gst.ElementFactory.make("capsfilter", "filter1")
if not filter1:
sys.stderr.write(" Unable to get the caps filter1 \n")
filter1.set_property("caps", caps1)
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")
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")
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', 1/30)
pgie.set_property('config-file-path', "dstest_imagedata_config.txt")
#Set properties of pgie and sgie
sgie1.set_property('config-file-path', "dstest2_sgie1_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("sync", 0)
if not is_aarch64():
# Use CUDA unified memory in the pipeline so frames
# can be easily accessed on CPU in Python.
mem_type = int(pyds.NVBUF_MEM_CUDA_UNIFIED)
streammux.set_property("nvbuf-memory-type", mem_type)
nvvidconv.set_property("nvbuf-memory-type", mem_type)
nvvidconv1.set_property("nvbuf-memory-type", mem_type)
tiler.set_property("nvbuf-memory-type", mem_type)
config = configparser.ConfigParser()
config.read('dstest2_tracker_config.txt')
config.sections()
for key in config['tracker']:
if key == 'tracker-width':
tracker_width = config.getint('tracker', key)
tracker.set_property('tracker-width', tracker_width)
if key == 'tracker-height' :
tracker_height = config.getint('tracker', key)
tracker.set_property('tracker-height', tracker_height)
if key == 'gpu-id' :
tracker_gpu_id = config.getint('tracker', key)
tracker.set_property('gpu_id', tracker_gpu_id)
if key == 'll-lib-file' :
tracker_ll_lib_file = config.get('tracker', key)
tracker.set_property('ll-lib-file', tracker_ll_lib_file)
if key == 'll-config-file' :
tracker_ll_config_file = config.get('tracker', key)
tracker.set_property('ll-config-file', tracker_ll_config_file)
if key == 'enable-batch-process' :
tracker_enable_batch_process = config.getint('tracker', key)
tracker.set_property('enable_batch_process', tracker_enable_batch_process)
print("Adding elements to Pipeline \n")
self.pipeline.add(pgie)
self.pipeline.add(tracker)
#self.pipeline.add(sgie1)
self.pipeline.add(tiler)
self.pipeline.add(nvvidconv)
self.pipeline.add(filter1)
self.pipeline.add(nvvidconv1)
self.pipeline.add(nvosd)
if is_aarch64():
self.pipeline.add(transform)
self.pipeline.add(sink)
print("Linking elements in the Pipeline \n")
streammux.link(pgie)
pgie.link(tracker)
tracker.link(nvvidconv1)
#pgie.link(nvvidconv1)
nvvidconv1.link(filter1)
filter1.link(tiler)
tiler.link(nvvidconv)
nvvidconv.link(nvosd)
if is_aarch64():
nvosd.link(transform)
transform.link(sink)
else:
nvosd.link(sink)
# create an event loop and feed gstreamer bus mesages to it
loop = GObject.MainLoop()
bus = self.pipeline.get_bus()
bus.add_signal_watch()
bus.connect ("message", bus_call, loop)
tiler_sink_pad=tiler.get_static_pad("sink")
if not tiler_sink_pad:
sys.stderr.write(" Unable to get src pad \n")
else:
tiler_sink_pad.add_probe(Gst.PadProbeType.BUFFER, self.tiler_sink_pad_buffer_probe, 0)
# List the sources
print("Now playing...")
for i, source in enumerate(args[:-1]):
if (i != 0):
print(i, ": ", source)
print("Starting pipeline \n")
# start play back and listed to events
self.pipeline.set_state(Gst.State.PLAYING)
try:
loop.run()
except:
pass
# cleanup
print("Exiting app\n")
self.pipeline.set_state(Gst.State.NULL)
