Nvidia Deepstream小细节系列：Deepstream python保存pipeline结构图

提示：此章节我们将着重阐述如何在Deepstream Python运行的情况下保存pipeline结构图。版本：Deepstream 6.0。

文章目录

Nvidia Deepstream小细节系列：Deepstream python保存pipeline结构图
- 步骤
- 代码（不重要，可跳过）
- 参考

步骤

首先安装依赖：sudo apt-get install graphviz。当然，需要确保你这个py文件是跑的起来的。

在你要运行的py文件import的部分添加：

import os
os.environ["GST_DEBUG_DUMP_DOT_DIR"] = "/tmp"
os.putenv('GST_DEBUG_DUMP_DIR_DIR', '/tmp')

最后，在文件中快开始允许loop之前添加Gst.debug_bin_to_dot_file(pipeline, Gst.DebugGraphDetails.ALL, "pipeline")，如下所示：

osdsinkpad.add_probe(Gst.PadProbeType.BUFFER, osd_sink_pad_buffer_probe, 0)Gst.debug_bin_to_dot_file(pipeline, Gst.DebugGraphDetails.ALL, "pipeline")# 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)

当我们这个py文件跑起来之后，在/tmp路径下就会出现一个pipeline.dot文件。

最后的最后，我们通过dot -Tpng pipeline.dot > pipeline.png将.dot文件转换为.png文件。打开后，你就能看到：

代码（不重要，可跳过）

这里附上python的源代码，其实就是deepstream_test_1.py加了两行：

#!/usr/bin/env python3
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_callimport pyds
import os
os.environ["GST_DEBUG_DUMP_DOT_DIR"] = "/tmp"
os.putenv('GST_DEBUG_DUMP_DIR_DIR', '/tmp')PGIE_CLASS_ID_VEHICLE = 0
PGIE_CLASS_ID_BICYCLE = 1
PGIE_CLASS_ID_PERSON = 2
PGIE_CLASS_ID_ROADSIGN = 3def osd_sink_pad_buffer_probe(pad,info,u_data):frame_number=0#Intiallizing object counter with 0.obj_counter = {PGIE_CLASS_ID_VEHICLE:0,PGIE_CLASS_ID_PERSON:0,PGIE_CLASS_ID_BICYCLE:0,PGIE_CLASS_ID_ROADSIGN:0}num_rects=0gst_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_listwhile 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:breakframe_number=frame_meta.frame_numnum_rects = frame_meta.num_obj_metal_obj=frame_meta.obj_meta_listwhile 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:breakobj_counter[obj_meta.class_id] += 1obj_meta.rect_params.border_color.set(0.0, 0.0, 1.0, 0.0)try: l_obj=l_obj.nextexcept 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 = 1py_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 appearpy_nvosd_text_params.x_offset = 10py_nvosd_text_params.y_offset = 12# Font , font-color and font-sizepy_nvosd_text_params.font_params.font_name = "Serif"py_nvosd_text_params.font_params.font_size = 10# set(red, green, blue, alpha); set to Whitepy_nvosd_text_params.font_params.font_color.set(1.0, 1.0, 1.0, 1.0)# Text background colorpy_nvosd_text_params.set_bg_clr = 1# set(red, green, blue, alpha); set to Blackpy_nvosd_text_params.text_bg_clr.set(0.0, 0.0, 0.0, 1.0)# Using pyds.get_string() to get display_text as stringprint(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.nextexcept StopIteration:breakreturn Gst.PadProbeReturn.OK def main(args):# Check input argumentsif len(args) != 2:sys.stderr.write("usage: %s <media file or uri>\n" % args[0])sys.exit(1)# Standard GStreamer initializationGObject.threads_init()Gst.init(None)# Create gstreamer elements# Create Pipeline element that will form a connection of other elementsprint("Creating Pipeline \n ")pipeline = Gst.Pipeline()if not pipeline:sys.stderr.write(" Unable to create Pipeline \n")# Source element for reading from the fileprint("Creating Source \n ")source = Gst.ElementFactory.make("filesrc", "file-source")if not source:sys.stderr.write(" Unable to create Source \n")# Since the data format in the input file is elementary h264 stream,# we need a h264parserprint("Creating H264Parser \n")h264parser = Gst.ElementFactory.make("h264parse", "h264-parser")if not h264parser:sys.stderr.write(" Unable to create h264 parser \n")# Use nvdec_h264 for hardware accelerated decode on GPUprint("Creating Decoder \n")decoder = Gst.ElementFactory.make("nvv4l2decoder", "nvv4l2-decoder")if not decoder:sys.stderr.write(" Unable to create Nvv4l2 Decoder \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 filepgie = 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 nvosdnvvidconv = Gst.ElementFactory.make("nvvideoconvert", "convertor")if not nvvidconv:sys.stderr.write(" Unable to create nvvidconv \n")# Create OSD to draw on the converted RGBA buffernvosd = Gst.ElementFactory.make("nvdsosd", "onscreendisplay")if not nvosd:sys.stderr.write(" Unable to create nvosd \n")# Finally render the osd outputif 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")print("Playing file %s " %args[1])source.set_property('location', 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', "dstest1_pgie_config.txt")print("Adding elements to Pipeline \n")pipeline.add(source)pipeline.add(h264parser)pipeline.add(decoder)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# file-source -> h264-parser -> nvh264-decoder -># nvinfer -> nvvidconv -> nvosd -> video-rendererprint("Linking elements in the Pipeline \n")source.link(h264parser)h264parser.link(decoder)sinkpad = streammux.get_request_pad("sink_0")if not sinkpad:sys.stderr.write(" Unable to get the sink pad of streammux \n")srcpad = decoder.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 an event loop and feed gstreamer bus mesages to itloop = 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)Gst.debug_bin_to_dot_file(pipeline, Gst.DebugGraphDetails.ALL, "pipeline")# start play back and listen to eventsprint("Starting pipeline \n")pipeline.set_state(Gst.State.PLAYING)try:loop.run()except:pass# cleanuppipeline.set_state(Gst.State.NULL)if __name__ == '__main__':sys.exit(main(sys.argv))

参考

参考1：deepstream保存pipeline图片
参考2：Python DeepStream program not generating dot file

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Nvidia Deepstream小细节系列：Deepstream python保存pipeline结构图

Nvidia Deepstream小细节系列：Deepstream python保存pipeline结构图

文章目录

步骤

代码（不重要，可跳过）

参考

Nvidia Deepstream小细节系列：Deepstream python保存pipeline结构图相关推荐

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