Jetson Nano
DeepStream 5.1
JetPack 4.5.1
TensorRT 7.1.3
I have an error when I run the file to run deepstream and the file is below. Looks like an error about building model .engine
import sys
sys.path.append(‘…/’)
import gi
gi.require_version(‘Gst’, ‘1.0’)
from gi.repository import GLib, Gst
from common.is_aarch_64 import is_aarch64
from common.bus_call import bus_call
from common.FPS import GETFPS
import configparser
from custom_retinaface import parse_objects_from_tensor_meta
import pyds
import numpy as np
import math
import time
import ctypes
ctypes.cdll.LoadLibrary(‘/opt/models/retinaface/libplugin_rface.so’)
def coor_scale(input_height, input_width, output_height, output_width):
return max(output_height/input_height, output_width/input_width)
def osd_sink_pad_buffer_probe(pad,info,u_data):
global scale
frame_number=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.glist_get_nvds_frame_meta()
# 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.glist_get_nvds_frame_meta(l_frame.data)
frame_meta = pyds.NvDsFrameMeta.cast(l_frame.data)
except StopIteration:
break
frame_number=frame_meta.frame_num
result_landmark = []
l_user=frame_meta.frame_user_meta_list
while l_user is not None:
try:
# Note that l_user.data needs a cast to pyds.NvDsUserMeta
# The casting is done by pyds.NvDsUserMeta.cast()
# The casting also keeps ownership of the underlying memory
# in the C code, so the Python garbage collector will leave
# it alone
user_meta=pyds.NvDsUserMeta.cast(l_user.data)
except StopIteration:
break
if(user_meta and user_meta.base_meta.meta_type==pyds.NvDsMetaType.NVDSINFER_TENSOR_OUTPUT_META):
try:
tensor_meta = pyds.NvDsInferTensorMeta.cast(user_meta.user_meta_data)
except StopIteration:
break
layer = pyds.get_nvds_LayerInfo(tensor_meta, 0)
result_boxes, result_scores, result_landmark = parse_objects_from_tensor_meta(layer)
# print(result_landmark)
try:
l_user=l_user.next
except StopIteration:
break
num_rects = frame_meta.num_obj_meta
face_count = 0
l_obj=frame_meta.obj_meta_list
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
# set bbox color in rgba
obj_meta.rect_params.border_color.set(1.0, 1.0, 1.0, 0.0)
# set the border width in pixel
obj_meta.rect_params.border_width=5
obj_meta.rect_params.has_bg_color=1
obj_meta.rect_params.bg_color.set(0.0, 0.5, 0.3, 0.4)
face_count +=1
#print(face_count)
try:
l_obj=l_obj.next
except StopIteration:
break
# Acquiring a display meta object. The memory ownership remains in
# the C code so downstream plugins can still access it. Otherwise
# the garbage collector will claim it when this probe function exits.
# draw 5 landmarks for each rect
# display_meta.num_circles = len(result_landmark) * 5
display_meta=pyds.nvds_acquire_display_meta_from_pool(batch_meta)
ccount = 0
for i in range(len(result_landmark)):
# scale coordinates
landmarks = result_landmark[i] * scale
# nvosd struct can only draw MAX 16 elements once
# so acquire a new display meta for every face detected
display_meta=pyds.nvds_acquire_display_meta_from_pool(batch_meta)
display_meta.num_circles = 5
ccount = 0
for j in range(5):
py_nvosd_circle_params = display_meta.circle_params[ccount]
py_nvosd_circle_params.circle_color.set(0.0, 0.0, 1.0, 1.0)
py_nvosd_circle_params.has_bg_color = 1
py_nvosd_circle_params.bg_color.set(0.0, 0.0, 0.0, 1.0)
py_nvosd_circle_params.xc = int(landmarks[j * 2]) if int(landmarks[j * 2]) > 0 else 0
py_nvosd_circle_params.yc = int(landmarks[j * 2 + 1]) if int(landmarks[j * 2 + 1]) > 0 else 0
py_nvosd_circle_params.radius=2
ccount = ccount + 1
pyds.nvds_add_display_meta_to_frame(frame_meta, display_meta)
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]
# Setting display text to be shown on screen
# Note that the pyds module allocates a buffer for the string, and the
# memory will not be claimed by the garbage collector.
# Reading the display_text field here will return the C address of the
# allocated string. Use pyds.get_string() to get the string content.
py_nvosd_text_params.display_text = "Frame Number={} Number of Objects={}".format(frame_number, num_rects)
# Now set the offsets where the string should appear
py_nvosd_text_params.x_offset = 10
py_nvosd_text_params.y_offset = 12
# Font , font-color and font-size
py_nvosd_text_params.font_params.font_name = "Serif"
py_nvosd_text_params.font_params.font_size = 10
# set(red, green, blue, alpha); set to White
py_nvosd_text_params.font_params.font_color.set(1.0, 1.0, 1.0, 1.0)
# Text background color
py_nvosd_text_params.set_bg_clr = 1
# set(red, green, blue, alpha); set to Black
py_nvosd_text_params.text_bg_clr.set(0.0, 0.0, 0.0, 1.0)
# Using pyds.get_string() to get display_text as string
# print(pyds.get_string(py_nvosd_text_params.display_text))
pyds.nvds_add_display_meta_to_frame(frame_meta, display_meta)
try:
l_frame=l_frame.next
except StopIteration:
break
return Gst.PadProbeReturn.OK
def main(args):
# Check input arguments
if len(args) != 2:
sys.stderr.write(“usage: %s \n” % args[0])
sys.exit(1)
global n_height, n_width, scale
n_height, n_width = 480, 640
scale = coor_scale(n_height, n_width, 1080, 1920)
# 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()
if not pipeline:
sys.stderr.write(" Unable to create Pipeline \n")
# Source element for reading from the file
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(" Unable to create v4l2src capsfilter \n")
print("Creating Video Converter \n")
# 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")
# 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")
# Use nvinfer to run inferencing on camera's output,
# behaviour of inferencing is set through config file
pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
if not pgie:
sys.stderr.write(" Unable to create pgie \n")
# Use convertor to convert from NV12 to RGBA as required by nvosd
nvvidconv = Gst.ElementFactory.make("nvvideoconvert", "convertor")
if not nvvidconv:
sys.stderr.write(" Unable to create nvvidconv \n")
# Create OSD to draw on the converted RGBA buffer
nvosd = Gst.ElementFactory.make("nvdsosd", "onscreendisplay")
if not nvosd:
sys.stderr.write(" Unable to create nvosd \n")
# Finally render the osd output
if is_aarch64():
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")
# 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")
# queue6=Gst.ElementFactory.make("queue","queue6")
# queue7=Gst.ElementFactory.make("queue","queue7")
# pipeline.add(queue1)
# pipeline.add(queue2)
# pipeline.add(queue3)
# pipeline.add(queue4)
# pipeline.add(queue5)
# pipeline.add(queue6)
# pipeline.add(queue7)
print("Playing cam %s " %args[1])
caps_v4l2src.set_property('caps', Gst.Caps.from_string("video/x-raw, framerate=30/1"))
caps_vidconvsrc.set_property('caps', Gst.Caps.from_string("video/x-raw(memory:NVMM)"))
source.set_property('device', args[1])
streammux.set_property('width', 1920)
streammux.set_property('height', 1080)
streammux.set_property('batch-size', 1)
streammux.set_property('batched-push-timeout', 4000000)
pgie.set_property('config-file-path', "config_ds_retinaface.txt")
pgie_batch_size=pgie.get_property("batch-size")
if(pgie_batch_size != 1):
print("WARNING: Overriding infer-config batch-size",pgie_batch_size," with number of sources ", 1," \n")
pgie.set_property("batch-size", pgie_batch_size)
# Set sync = false to avoid late frame drops at the display-sink
sink.set_property('sync', False)
print("Adding elements to Pipeline \n")
pipeline.add(source)
pipeline.add(caps_v4l2src)
pipeline.add(vidconvsrc)
pipeline.add(nvvidconvsrc)
pipeline.add(caps_vidconvsrc)
pipeline.add(streammux)
pipeline.add(pgie)
pipeline.add(nvvidconv)
pipeline.add(nvosd)
pipeline.add(sink)
# we link the elements together
# v4l2src -> nvvideoconvert -> mux ->
# nvinfer -> nvvideoconvert -> nvosd -> video-renderer
print("Linking elements in the Pipeline \n")
source.link(caps_v4l2src)
caps_v4l2src.link(vidconvsrc)
vidconvsrc.link(nvvidconvsrc)
nvvidconvsrc.link(caps_vidconvsrc)
sinkpad = streammux.get_request_pad("sink_0")
if not sinkpad:
sys.stderr.write(" Unable to get the sink pad of streammux \n")
srcpad = caps_vidconvsrc.get_static_pad("src")
if not srcpad:
sys.stderr.write(" Unable to get source pad of caps_vidconvsrc \n")
srcpad.link(sinkpad)
streammux.link(pgie)
pgie.link(nvvidconv)
nvvidconv.link(nvosd)
nvosd.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)
# Lets add probe to get informed of the meta data generated, we add probe to
# the sink pad of the osd element, since by that time, the buffer would have
# had got all the metadata.
osdsinkpad = nvosd.get_static_pad("sink")
if not osdsinkpad:
sys.stderr.write(" Unable to get sink pad of nvosd \n")
osdsinkpad.add_probe(Gst.PadProbeType.BUFFER, osd_sink_pad_buffer_probe, 0)
# start play back and listen to events
print("Starting pipeline \n")
pipeline.set_state(Gst.State.PLAYING)
try:
loop.run()
except:
pass
# cleanup
pipeline.set_state(Gst.State.NULL)
if name == ‘main’:
sys.exit(main(sys.argv))