• Hardware Platform (Jetson / GPU)
Jetson Orin
• DeepStream Version
6.1.1
• JetPack Version (valid for Jetson only)
5.0.2
• TensorRT Version
8.4.1-1+cuda11.4
I implemented nvdsanalytics my ALPR deepstream application to only detect vehicles withing ROI.
My pipeline:
streammux.link(q)
q.link(pgie)
pgie.link(nvanalytics) # I also tried after tracker
nvanalytics.link(tracker)
tracker.link(nvvidconvert_pre)
nvvidconvert_pre.link(filter1_pre)
filter1_pre.link(sgie1)
sgie1.link(preprocessing)
preprocessing.link(sgie2)
sgie2.link(tee)
queue1.link(msgconv)
msgconv.link(msgbroker)
queue2.link(nvstreamdemux)
......
# I need to get probe from sgie2 because I need to send all detections in Kafka with the correspondong parent ID
sgie2_sink_pad = sgie2.get_static_pad("src")
sgie2_sink_pad.add_probe(Gst.PadProbeType.BUFFER, osd_sink_pad_buffer_probe, 0)
.........
def nvanalytics_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:
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
}
print("#"*50)
while l_obj:
try:
# Note that l_obj.data needs a cast to pyds.NvDsObjectMeta
# The casting is done by pyds.NvDsObjectMeta.cast()
obj_meta=pyds.NvDsObjectMeta.cast(l_obj.data)
except StopIteration:
break
obj_counter[obj_meta.class_id] += 1
l_user_meta = obj_meta.obj_user_meta_list
# Extract object level meta data from NvDsAnalyticsObjInfo
while l_user_meta:
try:
user_meta = pyds.NvDsUserMeta.cast(l_user_meta.data)
if user_meta.base_meta.meta_type == pyds.nvds_get_user_meta_type("NVIDIA.DSANALYTICSOBJ.USER_META"):
user_meta_data = pyds.NvDsAnalyticsObjInfo.cast(user_meta.user_meta_data)
if user_meta_data.dirStatus: print("Object {0} moving in direction: {1}".format(obj_meta.object_id, user_meta_data.dirStatus))
if user_meta_data.lcStatus: print("Object {0} line crossing status: {1}".format(obj_meta.object_id, user_meta_data.lcStatus))
if user_meta_data.ocStatus: print("Object {0} overcrowding status: {1}".format(obj_meta.object_id, user_meta_data.ocStatus))
if user_meta_data.roiStatus: print("Object {0} roi status: {1}".format(obj_meta.object_id, user_meta_data.roiStatus))
except StopIteration:
break
try:
l_user_meta = l_user_meta.next
except StopIteration:
break
try:
l_obj=l_obj.next
except StopIteration:
break
# Get meta data from NvDsAnalyticsFrameMeta
l_user = frame_meta.frame_user_meta_list
while l_user:
try:
user_meta = pyds.NvDsUserMeta.cast(l_user.data)
if user_meta.base_meta.meta_type == pyds.nvds_get_user_meta_type("NVIDIA.DSANALYTICSFRAME.USER_META"):
user_meta_data = pyds.NvDsAnalyticsFrameMeta.cast(user_meta.user_meta_data)
if user_meta_data.objInROIcnt: print("Objs in ROI: {0}".format(user_meta_data.objInROIcnt))
if user_meta_data.objLCCumCnt: print("Linecrossing Cumulative: {0}".format(user_meta_data.objLCCumCnt))
if user_meta_data.objLCCurrCnt: print("Linecrossing Current Frame: {0}".format(user_meta_data.objLCCurrCnt))
if user_meta_data.ocStatus: print("Overcrowding status: {0}".format(user_meta_data.ocStatus))
except StopIteration:
break
try:
l_user = l_user.next
except StopIteration:
break
print("Frame Number=", frame_number, "stream id=", frame_meta.pad_index, "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
print("#"*50)
return Gst.PadProbeReturn.OK
config:
# The values in the config file are overridden by values set through GObject
# properties.
[property]
enable=1
#Width height used for configuration to which below configs are configured
config-width=1920
config-height=1080
#osd-mode 0: Dont display any lines, rois and text
# 1: Display only lines, rois and static text i.e. labels
# 2: Display all info from 1 plus information about counts
osd-mode=2
#Set OSD font size that has to be displayed
display-font-size=12
## Per stream configuration
[roi-filtering-stream-0]
#enable or disable following feature
enable=1
#ROI to filter select objects, and remove from meta data
roi-RF=100;5;100;1050;1820;5;1820;1050
#remove objects in the ROI
inverse-roi=0
class-id=-1
Output:
Also I tried adding nvdsanalytics after my third detector (OCR) and doing nvdsanalytics_sink_pad = nvdsanalytics.get_static_pad("src") but it only recognizes objects from the secondary and third detector, objects,from the first detector do not show up.