使用 deepstream_app_config_yoloV3.txt 和 TRT 引擎文件 fp16.engine，我在 yolov3-spp 上的 FPS 为 15，在 yolov3-tiny 上的 FPS 为 30。
我的问题是：有没有办法重新创建我在 python deepstream 自定义应用程序上运行 deepstream_app_config_yoloV3.txt的fps ？
因为我想提取检测到的对象名称和边界框坐标等元数据。如果我可以在deepstream_app_config_yoloV3.txt 应用程序（而不是 custom-app.py 脚本）上执行此操作，我将非常乐意放弃 python 脚本
我的设置：
Jetson Nano B01
Deep-stream 5.0
Jetpack 4.4
摄像头：CSI Pi-camera V2
这是 deepstream-app-test1 的修改版本，其中我更改了 Pi-cam 的源而不是视频文件。
在运行自定义应用程序时，由于有线批处理问题，我得到了大约 5 fps。我应该修改什么来停止这种批处理并增加 fps 吗？
我添加了一个“fps = 30/1”的参数，看看它是否会有所作为，但它并没有停止批处理
我的代码：
import sys
sys.path.append('../')
import gi
gi.require_version('Gst', '1.0')
from gi.repository import GObject, Gst
from common.is_aarch_64 import is_aarch64
from common.bus_call import bus_call
import pyds
PGIE_CLASS_ID_TOOTHBRUSH = 80
PGIE_CLASS_ID_HAIR_DRYER = 79
PGIE_CLASS_ID_TEDDY_BEAR = 78
PGIE_CLASS_ID_SCISSORS = 77
PGIE_CLASS_ID_VASE = 76
PGIE_CLASS_ID_CLOCK = 75
PGIE_CLASS_ID_BOOK = 74
PGIE_CLASS_ID_REFRIGERATOR = 73
PGIE_CLASS_ID_SINK = 72
PGIE_CLASS_ID_TOASTER = 71
PGIE_CLASS_ID_OVEN = 70
PGIE_CLASS_ID_MICROWAVE = 69
PGIE_CLASS_ID_CELL_PHONE = 68
PGIE_CLASS_ID_KEYBOARD = 67
PGIE_CLASS_ID_REMOTE = 66
PGIE_CLASS_ID_MOUSE = 65
PGIE_CLASS_ID_LAPTOP = 64
PGIE_CLASS_ID_TVMONITOR = 63
PGIE_CLASS_ID_TOILET = 62
PGIE_CLASS_ID_DININGTABLE= 61
PGIE_CLASS_ID_BED = 60
PGIE_CLASS_ID_POTTEDPLANT = 59
PGIE_CLASS_ID_SOFA = 58
PGIE_CLASS_ID_CHAIR = 57
PGIE_CLASS_ID_CAKE = 56
PGIE_CLASS_ID_DONUT = 55
PGIE_CLASS_ID_PIZZA = 54
PGIE_CLASS_ID_HOT_DOG = 53
PGIE_CLASS_ID_CARROT = 52
PGIE_CLASS_ID_BROCCOLI = 51
PGIE_CLASS_ID_ORANGE = 50
PGIE_CLASS_ID_SANDWICH = 49
PGIE_CLASS_ID_APPLE = 48
PGIE_CLASS_ID_BANANA = 47
PGIE_CLASS_ID_BOWL = 46
PGIE_CLASS_ID_SPOON = 45
PGIE_CLASS_ID_KNIFE = 44
PGIE_CLASS_ID_FORK = 43
PGIE_CLASS_ID_CUP = 42
PGIE_CLASS_ID_WINE_GLASS = 41
PGIE_CLASS_ID_BOTTLE = 40
PGIE_CLASS_ID_TENNIS_RACKET = 39
PGIE_CLASS_ID_SURFBOARD = 38
PGIE_CLASS_ID_SKATEBOARD = 37
PGIE_CLASS_ID_BASEBALL_GLOVE = 36
PGIE_CLASS_ID_BASEBALL_BAT = 35
PGIE_CLASS_ID_KITE = 34
PGIE_CLASS_ID_SPORTS_BALL = 33
PGIE_CLASS_ID_SNOWBOARD = 32
PGIE_CLASS_ID_SKIS = 31
PGIE_CLASS_ID_FRISBEE = 30
PGIE_CLASS_ID_SUITCASE = 29
PGIE_CLASS_ID_TIE = 28
PGIE_CLASS_ID_HANDBAG = 27
PGIE_CLASS_ID_UMBRELLA = 26
PGIE_CLASS_ID_BACKPACK = 25
PGIE_CLASS_ID_UMBRELLA = 24
PGIE_CLASS_ID_GIRAFFE = 23
PGIE_CLASS_ID_ZEBRA = 22
PGIE_CLASS_ID_BEAR = 21
PGIE_CLASS_ID_ELEPHANT = 20
PGIE_CLASS_ID_COW = 19
PGIE_CLASS_ID_SHEEP = 18
PGIE_CLASS_ID_HORSE = 17
PGIE_CLASS_ID_DOG = 16
PGIE_CLASS_ID_CAT = 15
PGIE_CLASS_ID_BIRD = 14
PGIE_CLASS_ID_BENCH = 13
PGIE_CLASS_ID_PARKING_METER = 12
PGIE_CLASS_ID_STOP_SIGN = 11
PGIE_CLASS_ID_FIRE_HYDRANT = 10
PGIE_CLASS_ID_TRAFFIC_LIGHT = 9
PGIE_CLASS_ID_BOAT = 8
PGIE_CLASS_ID_TRUCK = 7
PGIE_CLASS_ID_TRAIN = 6
PGIE_CLASS_ID_BUS = 5
PGIE_CLASS_ID_AEROPLANE = 4
PGIE_CLASS_ID_MOTORBIKE = 3
PGIE_CLASS_ID_VEHICLE = 2
PGIE_CLASS_ID_BICYCLE = 1
PGIE_CLASS_ID_PERSON = 0
pgie_classes_str= ["Toothbrush", "Hair dryer", "Teddy bear","Scissors","Vase", "Clock", "Book","Refrigerator", "Sink", "Toaster","Oven","Microwave", "Cell phone", "Keyboard","Remote", "Mouse", "Laptop","Tvmonitor","Toilet", "Diningtable", "Bed","Pottedplant", "Sofa", "Chair","Cake","Donut", "Pizza", "Hot dog","Carrot", "Broccli", "Orange","Sandwich","Apple", "Banana", "Bowl","Spoon", "Knife", "Fork","Cup","Wine Glass", "Bottle", "Tennis racket","Surfboard", "Skateboard", "Baseball glove","Baseball bat","Kite", "Sports ball", "Snowboard","Skis", "Frisbee", "Suitcase","Tie","Handbag", "Umbrella", "Backpack","Giraffe", "Zebra", "Bear","Elephant","Cow", "Sheep", "Horse","Dog", "Cat", "Bird","Bench","Parking meter", "Stop sign", "Fire hydrant","Traffic light", "Boat", "Truck","Train","Bus", "Areoplane", "Motorbike","Car", "Bicycle", "Person"]
def osd_sink_pad_buffer_probe(pad,info,u_data):
frame_number=0
#Intiallizing object counter with 0.
obj_counter = {
PGIE_CLASS_ID_TOOTHBRUSH:0,
PGIE_CLASS_ID_HAIR_DRYER:0,
PGIE_CLASS_ID_TEDDY_BEAR:0,
PGIE_CLASS_ID_SCISSORS:0,
PGIE_CLASS_ID_VASE:0,
PGIE_CLASS_ID_CLOCK:0,
PGIE_CLASS_ID_BOOK:0,
PGIE_CLASS_ID_REFRIGERATOR:0,
PGIE_CLASS_ID_SINK:0,
PGIE_CLASS_ID_TOASTER:0,
PGIE_CLASS_ID_OVEN:0,
PGIE_CLASS_ID_MICROWAVE:0,
PGIE_CLASS_ID_CELL_PHONE:0,
PGIE_CLASS_ID_KEYBOARD:0,
PGIE_CLASS_ID_REMOTE:0,
PGIE_CLASS_ID_MOUSE:0,
PGIE_CLASS_ID_LAPTOP:0,
PGIE_CLASS_ID_TVMONITOR:0,
PGIE_CLASS_ID_TOILET:0,
PGIE_CLASS_ID_DININGTABLE:0,
PGIE_CLASS_ID_BED:0,
PGIE_CLASS_ID_POTTEDPLANT:0,
PGIE_CLASS_ID_SOFA:0,
PGIE_CLASS_ID_CHAIR:0,
PGIE_CLASS_ID_CAKE:0,
PGIE_CLASS_ID_DONUT:0,
PGIE_CLASS_ID_PIZZA:0,
PGIE_CLASS_ID_HOT_DOG:0,
PGIE_CLASS_ID_CARROT:0,
PGIE_CLASS_ID_BROCCOLI:0,
PGIE_CLASS_ID_ORANGE:0,
PGIE_CLASS_ID_SANDWICH:0,
PGIE_CLASS_ID_APPLE:0,
PGIE_CLASS_ID_BANANA:0,
PGIE_CLASS_ID_BOWL:0,
PGIE_CLASS_ID_SPOON:0,
PGIE_CLASS_ID_KNIFE:0,
PGIE_CLASS_ID_FORK:0,
PGIE_CLASS_ID_CUP:0,
PGIE_CLASS_ID_WINE_GLASS:0,
PGIE_CLASS_ID_BOTTLE:0,
PGIE_CLASS_ID_TENNIS_RACKET:0,
PGIE_CLASS_ID_SURFBOARD:0,
PGIE_CLASS_ID_SKATEBOARD:0,
PGIE_CLASS_ID_BASEBALL_GLOVE:0,
PGIE_CLASS_ID_BASEBALL_BAT:0,
PGIE_CLASS_ID_KITE:0,
PGIE_CLASS_ID_SPORTS_BALL:0,
PGIE_CLASS_ID_SNOWBOARD:0,
PGIE_CLASS_ID_SKIS:0,
PGIE_CLASS_ID_FRISBEE:0,
PGIE_CLASS_ID_SUITCASE:0,
PGIE_CLASS_ID_TIE:0,
PGIE_CLASS_ID_HANDBAG:0,
PGIE_CLASS_ID_UMBRELLA:0,
PGIE_CLASS_ID_BACKPACK:0,
PGIE_CLASS_ID_UMBRELLA:0,
PGIE_CLASS_ID_GIRAFFE:0,
PGIE_CLASS_ID_ZEBRA:0,
PGIE_CLASS_ID_BEAR:0,
PGIE_CLASS_ID_ELEPHANT:0,
PGIE_CLASS_ID_COW:0,
PGIE_CLASS_ID_SHEEP:0,
PGIE_CLASS_ID_HORSE:0,
PGIE_CLASS_ID_DOG:0,
PGIE_CLASS_ID_CAT:0,
PGIE_CLASS_ID_BIRD:0,
PGIE_CLASS_ID_BENCH:0,
PGIE_CLASS_ID_PARKING_METER:0,
PGIE_CLASS_ID_STOP_SIGN:0,
PGIE_CLASS_ID_FIRE_HYDRANT:0,
PGIE_CLASS_ID_TRAFFIC_LIGHT:0,
PGIE_CLASS_ID_BOAT:0,
PGIE_CLASS_ID_TRUCK:0,
PGIE_CLASS_ID_TRAIN:0,
PGIE_CLASS_ID_BUS:0,
PGIE_CLASS_ID_AEROPLANE:0,
PGIE_CLASS_ID_MOTORBIKE:0,
PGIE_CLASS_ID_VEHICLE:0,
PGIE_CLASS_ID_BICYCLE:0,
PGIE_CLASS_ID_PERSON: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.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
num_rects = frame_meta.num_obj_meta
l_obj=frame_meta.obj_meta_list
while l_obj is not None:
try:
# Casting l_obj.data to pyds.NvDsObjectMeta
#obj_meta=pyds.glist_get_nvds_object_meta(l_obj.data)
obj_meta=pyds.NvDsObjectMeta.cast(l_obj.data)
except StopIteration:
break
obj_counter[obj_meta.class_id] += 1
obj_meta.rect_params.border_color.set(0.0, 0.0, 1.0, 0.0)
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.
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={} Vehicle_count={} Person_count={}".format(frame_number, num_rects, obj_counter[PGIE_CLASS_ID_VEHICLE], obj_counter[PGIE_CLASS_ID_PERSON])
# 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):
# 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()
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("nvarguscamerasrc", "src-elem")
if not source:
sys.stderr.write(" Unable to create Source \n")
# Converter to scale the image
nvvidconv_src = Gst.ElementFactory.make("nvvideoconvert", "convertor_src")
if not nvvidconv_src:
sys.stderr.write(" Unable to create nvvidconv_src \n")
# Caps for NVMM and resolution scaling
caps_nvvidconv_src = Gst.ElementFactory.make("capsfilter", "nvmm_caps")
if not caps_nvvidconv_src:
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 decoder'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():
transform = Gst.ElementFactory.make("nvegltransform", "nvegl-transform")
print("Creating EGLSink \n")
sink = Gst.ElementFactory.make("nveglglessink", "nvvideo-renderer")
if not sink:
sys.stderr.write(" Unable to create egl sink \n")
source.set_property('bufapi-version', True)
caps_nvvidconv_src.set_property('caps', Gst.Caps.from_string('video/x-raw(memory:NVMM), width=720, height=480, framerate=30/1'))
streammux.set_property('width', 720)
streammux.set_property('height', 480)
streammux.set_property('batch-size', 1)
streammux.set_property('batched-push-timeout', 4000000)
pgie.set_property('config-file-path', "config_infer_primary_yoloV3.txt")
print("Adding elements to Pipeline \n")
pipeline.add(source)
pipeline.add(nvvidconv_src)
pipeline.add(caps_nvvidconv_src)
pipeline.add(streammux)
pipeline.add(pgie)
pipeline.add(nvvidconv)
pipeline.add(nvosd)
pipeline.add(sink)
if is_aarch64():
pipeline.add(transform)
# we link the elements together
# Csi camera -> -nvvidconv_src -> caps_nvvidconv_src ->
# nvinfer (pgie)-> nvvidconv -> nvosd -> video-renderer
print("Linking elements in the Pipeline \n")
source.link(nvvidconv_src)
nvvidconv_src.link(caps_nvvidconv_src)
sinkpad = streammux.get_request_pad("sink_0")
if not sinkpad:
sys.stderr.write(" Unable to get the sink pad of streammux \n")
srcpad = caps_nvvidconv_src.get_static_pad("src")
if not srcpad:
sys.stderr.write(" Unable to get source pad of decoder \n")
srcpad.link(sinkpad)
streammux.link(pgie)
pgie.link(nvvidconv)
nvvidconv.link(nvosd)
if is_aarch64():
nvosd.link(transform)
transform.link(sink)
else:
nvosd.link(sink)
# create and event loop and feed gstreamer bus mesages
loop = GObject.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)
print("Starting pipeline \n")
# start play back and listed to events
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))