蚕茧视频识别AI程序关键代码（不包含资源、模型、转换库）
This commit is contained in:
BBIT-Kai
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#!/usr/bin/env python3
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################################################################################
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# SPDX-FileCopyrightText: Copyright (c) 2019-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: Apache-2.0
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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################################################################################
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import sys
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from pathlib import Path
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SCRIPT_DIR = Path(__file__).resolve().parent # apps/mine
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DEEPSTREAM_PY_DIR = SCRIPT_DIR.parent # deepstream_python_apps
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sys.path.insert(0, str(DEEPSTREAM_PY_DIR)) # common/ 在这里
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sys.path.insert(0, str(DEEPSTREAM_PY_DIR / "pyds")) # pyds 模块
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from pathlib import Path
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from os import environ
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import gi
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import configparser
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import argparse
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gi.require_version('Gst', '1.0')
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from gi.repository import GLib, Gst
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from ctypes import *
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import time
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import sys
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import math
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import platform
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from common.platform_info import PlatformInfo
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from common.bus_call import bus_call
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from common.FPS import PERF_DATA
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import pyds
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import sys
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from pathlib import Path
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from sources.dev.app.utils.my_utils import *
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display_type = 0
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silent = False
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file_loop = False
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perf_data = None
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measure_latency = False
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MAX_DISPLAY_LEN=64
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PGIE_CLASS_ID_NORMAL = 0
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PGIE_CLASS_ID_DOUBLE_PUPA = 1
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PGIE_CLASS_ID_SPOT = 2
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PGIE_CLASS_ID_HAIRY = 3
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PGIE_CLASS_ID_MAGGOT_SHELL = 4
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MUXER_OUTPUT_WIDTH=1920
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MUXER_OUTPUT_HEIGHT=1080
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MUXER_BATCH_TIMEOUT_USEC = 33000
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TILED_OUTPUT_WIDTH=1280
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TILED_OUTPUT_HEIGHT=720
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YOLO_SIZE=768
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GST_CAPS_FEATURES_NVMM="memory:NVMM"
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OSD_PROCESS_MODE= 0
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OSD_DISPLAY_TEXT= 1
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pgie_classes_str= ["Vehicle", "TwoWheeler", "Person","RoadSign"]
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count_sc = 0
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od_labels = []
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with open("../models/labels.txt", "r") as f:
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od_labels = [line.strip() for line in f.readlines()]
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def add_fps_display_meta(lineCount, batch_meta, frame_meta, display_text):
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display_meta=pyds.nvds_acquire_display_meta_from_pool(batch_meta)
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display_meta.num_labels = 1
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py_nvosd_text_params = display_meta.text_params[0]
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py_nvosd_text_params.display_text = display_text
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py_nvosd_text_params.x_offset = 12
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py_nvosd_text_params.y_offset = 12 + lineCount * 24
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py_nvosd_text_params.font_params.font_name = "Serif"
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py_nvosd_text_params.font_params.font_size = 10
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py_nvosd_text_params.font_params.font_color.set(1.0, 1.0, 1.0, 1.0)
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py_nvosd_text_params.set_bg_clr = 1
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py_nvosd_text_params.text_bg_clr.set(0.0, 0.0, 0.0, 1.0)
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# print(pyds.get_string(py_nvosd_text_params.display_text))
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pyds.nvds_add_display_meta_to_frame(frame_meta, display_meta)
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# pgie_src_pad_buffer_probe will extract metadata received on tiler sink pad
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# and update params for drawing rectangle, object information etc.
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def pgie_src_pad_buffer_probe(pad,info,u_data):
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frame_number=0
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num_rects=0
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got_fps = False
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gst_buffer = info.get_buffer()
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if not gst_buffer:
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print("Unable to get GstBuffer ")
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return
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# Retrieve batch metadata from the gst_buffer
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# Note that pyds.gst_buffer_get_nvds_batch_meta() expects the
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# C address of gst_buffer as input, which is obtained with hash(gst_buffer)
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# Enable latency measurement via probe if environment variable NVDS_ENABLE_LATENCY_MEASUREMENT=1 is set.
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# To enable component level latency measurement, please set environment variable
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# NVDS_ENABLE_COMPONENT_LATENCY_MEASUREMENT=1 in addition to the above.
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global measure_latency
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if measure_latency:
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num_sources_in_batch = pyds.nvds_measure_buffer_latency(hash(gst_buffer))
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if num_sources_in_batch == 0:
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print("Unable to get number of sources in GstBuffer for latency measurement")
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batch_meta = pyds.gst_buffer_get_nvds_batch_meta(hash(gst_buffer))
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l_frame = batch_meta.frame_meta_list
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global count_sc
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while l_frame is not None:
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try:
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# Note that l_frame.data needs a cast to pyds.NvDsFrameMeta
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# The casting is done by pyds.NvDsFrameMeta.cast()
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# The casting also keeps ownership of the underlying memory
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# in the C code, so the Python garbage collector will leave
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# it alone.
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frame_meta = pyds.NvDsFrameMeta.cast(l_frame.data)
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except StopIteration:
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break
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frame_number=frame_meta.frame_num
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l_obj=frame_meta.obj_meta_list
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num_rects = frame_meta.num_obj_meta
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obj_counter = {
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PGIE_CLASS_ID_NORMAL:0,
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PGIE_CLASS_ID_SPOT:0,
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PGIE_CLASS_ID_DOUBLE_PUPA:0,
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PGIE_CLASS_ID_HAIRY:0,
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PGIE_CLASS_ID_MAGGOT_SHELL:0
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}
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while l_obj is not None:
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try:
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# Casting l_obj.data to pyds.NvDsObjectMeta
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obj_meta=pyds.NvDsObjectMeta.cast(l_obj.data)
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except StopIteration:
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break
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obj_counter[obj_meta.class_id] += 1
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try:
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l_obj=l_obj.next
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except StopIteration:
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break
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# if not silent:
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# print("帧ID=", frame_number, "总蚕茧数=",num_rects,"正茧数=",obj_counter[PGIE_CLASS_ID_NORMAL],"黄斑茧数=",obj_counter[PGIE_CLASS_ID_SPOT])
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# Update frame rate through this probe
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stream_index = "stream{0}".format(frame_meta.pad_index)
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global perf_data
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perf_data.update_fps(stream_index)
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text = f"Object Count: {num_rects}\n"
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for i in range(len(od_labels)):
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if obj_counter[i] > 0:
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text += f"\t{od_labels[i]}: {obj_counter[i]}\n"
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add_fps_display_meta(0,batch_meta,frame_meta, text)
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try:
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l_frame=l_frame.next
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except StopIteration:
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break
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# Multi Object Tracker----------------------------------------------------
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l_obj=batch_meta.batch_user_meta_list
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while l_obj is not None:
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try:
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user_meta=pyds.NvDsUserMeta.cast(l_obj.data)
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except StopIteration:
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break
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# 遍历user_meta.base_meta.meta_type
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if user_meta and user_meta.base_meta.meta_type==pyds.NvDsMetaType.NVDS_TRACKER_PAST_FRAME_META :
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try:
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pPastDataBatch = pyds.NvDsTargetMiscDataBatch.cast(user_meta.user_meta_data)
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except StopIteration:
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break
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for miscDataStream in pyds.NvDsTargetMiscDataBatch.list(pPastDataBatch):
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for miscDataObj in pyds.NvDsTargetMiscDataStream.list(miscDataStream):
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unique_id = miscDataObj.uniqueId
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if unique_id > count_sc:
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count_sc = unique_id
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try:
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l_obj=l_obj.next
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except StopIteration:
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break
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return Gst.PadProbeReturn.OK
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def cb_newpad(decodebin, decoder_src_pad,data):
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print("In cb_newpad\n")
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caps=decoder_src_pad.get_current_caps()
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if not caps:
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caps = decoder_src_pad.query_caps()
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gststruct=caps.get_structure(0)
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gstname=gststruct.get_name()
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source_bin=data
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features=caps.get_features(0)
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# Need to check if the pad created by the decodebin is for video and not
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# audio.
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print("gstname=",gstname)
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if(gstname.find("video")!=-1):
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# Link the decodebin pad only if decodebin has picked nvidia
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# decoder plugin nvdec_*. We do this by checking if the pad caps contain
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# NVMM memory features.
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print("features=",features)
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if features.contains("memory:NVMM"):
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# Get the source bin ghost pad
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bin_ghost_pad=source_bin.get_static_pad("src")
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if not bin_ghost_pad.set_target(decoder_src_pad):
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sys.stderr.write("Failed to link decoder src pad to source bin ghost pad\n")
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else:
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sys.stderr.write(" Error: Decodebin did not pick nvidia decoder plugin.\n")
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def decodebin_child_added(child_proxy,Object,name,user_data):
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print("Decodebin child added:", name, "\n")
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if(name.find("decodebin") != -1):
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Object.connect("child-added",decodebin_child_added,user_data)
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if "source" in name:
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source_element = child_proxy.get_by_name("source")
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if source_element.find_property('drop-on-latency') != None:
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Object.set_property("drop-on-latency", True)
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def create_source_bin(index,uri):
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print("Creating source bin")
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# Create a source GstBin to abstract this bin's content from the rest of the
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# pipeline
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bin_name="source-bin-%02d" %index
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print(bin_name)
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nbin=Gst.Bin.new(bin_name)
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if not nbin:
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sys.stderr.write(" Unable to create source bin \n")
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# Source element for reading from the uri.
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# We will use decodebin and let it figure out the container format of the
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# stream and the codec and plug the appropriate demux and decode plugins.
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if file_loop:
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# use nvurisrcbin to enable file-loop
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uri_decode_bin=Gst.ElementFactory.make("nvurisrcbin", "uri-decode-bin")
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uri_decode_bin.set_property("file-loop", 1)
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uri_decode_bin.set_property("cudadec-memtype", 0)
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else:
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uri_decode_bin=Gst.ElementFactory.make("uridecodebin", "uri-decode-bin")
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if not uri_decode_bin:
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sys.stderr.write(" Unable to create uri decode bin \n")
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# We set the input uri to the source element
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uri_decode_bin.set_property("uri",uri)
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# Connect to the "pad-added" signal of the decodebin which generates a
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# callback once a new pad for raw data has beed created by the decodebin
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uri_decode_bin.connect("pad-added",cb_newpad,nbin)
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uri_decode_bin.connect("child-added",decodebin_child_added,nbin)
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# We need to create a ghost pad for the source bin which will act as a proxy
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# for the video decoder src pad. The ghost pad will not have a target right
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# now. Once the decode bin creates the video decoder and generates the
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# cb_newpad callback, we will set the ghost pad target to the video decoder
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# src pad.
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Gst.Bin.add(nbin,uri_decode_bin)
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bin_pad=nbin.add_pad(Gst.GhostPad.new_no_target("src",Gst.PadDirection.SRC))
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if not bin_pad:
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sys.stderr.write(" Failed to add ghost pad in source bin \n")
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return None
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return nbin
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def main(args, requested_pgie=None, config=None, disable_probe=False):
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global perf_data,TILED_OUTPUT_WIDTH,TILED_OUTPUT_HEIGHT,YOLO_SIZE,count_sc
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perf_data = PERF_DATA(len(args))
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number_sources=len(args)
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if number_sources == 1:
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print("重置输出分辨率至:{} x {}".format(TILED_OUTPUT_WIDTH, TILED_OUTPUT_HEIGHT))
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TILED_OUTPUT_WIDTH, TILED_OUTPUT_HEIGHT = getVideoResolution(stream_paths[0])
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platform_info = PlatformInfo()
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# Standard GStreamer initialization
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Gst.init(None)
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# Create gstreamer elements */
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# Create Pipeline element that will form a connection of other elements
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print("Creating Pipeline \n ")
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pipeline = Gst.Pipeline()
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is_live = False
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if not pipeline:
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sys.stderr.write(" Unable to create Pipeline \n")
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print("Creating streamux \n ")
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# Create nvstreammux instance to form batches from one or more sources.
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nvstreammux = Gst.ElementFactory.make("nvstreammux", "Stream-muxer")
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if not nvstreammux:
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sys.stderr.write(" Unable to create NvStreamMux \n")
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pipeline.add(nvstreammux)
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for i in range(number_sources):
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print("Creating source_bin ",i," \n ")
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uri_name=args[i]
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if uri_name.find("rtsp://") == 0 :
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is_live = True
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source_bin=create_source_bin(i, uri_name)
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if not source_bin:
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sys.stderr.write("Unable to create source bin \n")
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pipeline.add(source_bin)
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padname="sink_%u" %i
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sinkpad= nvstreammux.request_pad_simple(padname)
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if not sinkpad:
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sys.stderr.write("Unable to create sink pad bin \n")
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srcpad=source_bin.get_static_pad("src")
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if not srcpad:
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sys.stderr.write("Unable to create src pad bin \n")
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srcpad.link(sinkpad)
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queue1=Gst.ElementFactory.make("queue","queue1")
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queue2=Gst.ElementFactory.make("queue","queue2")
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queue3=Gst.ElementFactory.make("queue","queue3")
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queue4=Gst.ElementFactory.make("queue","queue4")
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queue5=Gst.ElementFactory.make("queue","queue5")
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pipeline.add(queue1)
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pipeline.add(queue2)
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pipeline.add(queue3)
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pipeline.add(queue4)
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pipeline.add(queue5)
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nvdslogger = None
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print("Creating Pgie \n ")
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if requested_pgie != None and (requested_pgie == 'nvinferserver' or requested_pgie == 'nvinferserver-grpc') :
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pgie = Gst.ElementFactory.make("nvinferserver", "primary-inference")
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elif requested_pgie != None and requested_pgie == 'nvinfer':
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# local tensorrt infer
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pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
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else:
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pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
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if not pgie:
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sys.stderr.write(" Unable to create pgie : %s\n" % requested_pgie)
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if disable_probe:
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# Use nvdslogger for perf measurement instead of probe function
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print ("Creating nvdslogger \n")
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nvdslogger = Gst.ElementFactory.make("nvdslogger", "nvdslogger")
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print("Creating tiler \n ")
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nvmultistreamtiler=Gst.ElementFactory.make("nvmultistreamtiler", "nvtiler")
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if not nvmultistreamtiler:
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sys.stderr.write(" Unable to create tiler \n")
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print("Creating nvvidconv \n ")
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nvvidconv = Gst.ElementFactory.make("nvvideoconvert", "convertor")
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if not nvvidconv:
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sys.stderr.write(" Unable to create nvvidconv \n")
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print("Creating nvosd \n ")
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nvosd = Gst.ElementFactory.make("nvdsosd", "onscreendisplay")
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if not nvosd:
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sys.stderr.write(" Unable to create nvosd \n")
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nvosd.set_property('process-mode',OSD_PROCESS_MODE)
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nvosd.set_property('display-text',OSD_DISPLAY_TEXT)
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if file_loop:
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if platform_info.is_integrated_gpu():
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# Set nvbuf-memory-type=4 for integrated gpu for file-loop (nvurisrcbin case)
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nvstreammux.set_property('nvbuf-memory-type', 4)
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else:
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# Set nvbuf-memory-type=2 for x86 for file-loop (nvurisrcbin case)
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nvstreammux.set_property('nvbuf-memory-type', 2)
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if display_type == 0:
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sink = Gst.ElementFactory.make("filesink", "file-sink")
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sink.set_property("location", "./out.mp4")
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sink.set_property("sync", 0)
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elif display_type == 1:
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print("Creating Fakesink \n")
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sink = Gst.ElementFactory.make("fakesink", "fakesink")
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sink.set_property('enable-last-sample', 0)
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sink.set_property('sync', 0)
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else:
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if platform_info.is_integrated_gpu():
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print("Creating nv3dsink \n")
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sink = Gst.ElementFactory.make("nv3dsink", "nv3d-sink")
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if not sink:
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sys.stderr.write(" Unable to create nv3dsink \n")
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else:
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if platform_info.is_platform_aarch64():
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print("Creating nv3dsink \n")
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sink = Gst.ElementFactory.make("nv3dsink", "nv3d-sink")
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else:
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print("Creating EGLSink \n")
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sink = Gst.ElementFactory.make("nveglglessink", "nvvideo-renderer")
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if not sink:
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sys.stderr.write(" Unable to create egl sink \n")
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if not sink:
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sys.stderr.write(" Unable to create sink element \n")
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if is_live:
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print("At least one of the sources is live")
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nvstreammux.set_property('live-source', 1)
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nvvidconv2 = Gst.ElementFactory.make("nvvideoconvert", "convertor2")
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if not nvvidconv2:
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sys.stderr.write(" Unable to create nvvidconv2 \n")
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encoder = Gst.ElementFactory.make("nvv4l2h264enc", "encoder") # for h264
|
||||
# encoder = Gst.ElementFactory.make("avenc_mpeg4", "encoder") # for mpeg4
|
||||
if not encoder:
|
||||
sys.stderr.write(" Unable to create encoder \n")
|
||||
encoder.set_property("bitrate", 2000000)
|
||||
|
||||
h264parse = Gst.ElementFactory.make("h264parse", "parser")
|
||||
# codeparser = Gst.ElementFactory.make("mpeg4videoparse", "mpeg4-parser")
|
||||
if not h264parse:
|
||||
sys.stderr.write(" Unable to create code parser \n")
|
||||
|
||||
qtmux = Gst.ElementFactory.make("qtmux", "qtmux")
|
||||
if not qtmux:
|
||||
sys.stderr.write(" Unable to create code parser \n")
|
||||
|
||||
nvstreammux.set_property('width', YOLO_SIZE)
|
||||
nvstreammux.set_property('height', YOLO_SIZE)
|
||||
nvstreammux.set_property('batch-size', number_sources)
|
||||
nvstreammux.set_property('batched-push-timeout', MUXER_BATCH_TIMEOUT_USEC)
|
||||
if requested_pgie == "nvinferserver" and config != None:
|
||||
pgie.set_property('config-file-path', config)
|
||||
elif requested_pgie == "nvinferserver-grpc" and config != None:
|
||||
pgie.set_property('config-file-path', config)
|
||||
elif requested_pgie == "nvinfer" and config != None:
|
||||
pgie.set_property('config-file-path', config)
|
||||
else:
|
||||
pgie.set_property('config-file-path', "config/pgie_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))
|
||||
nvmultistreamtiler.set_property("rows",tiler_rows)
|
||||
nvmultistreamtiler.set_property("columns",tiler_columns)
|
||||
nvmultistreamtiler.set_property("width", TILED_OUTPUT_WIDTH)
|
||||
nvmultistreamtiler.set_property("height", TILED_OUTPUT_HEIGHT)
|
||||
if platform_info.is_integrated_gpu():
|
||||
nvmultistreamtiler.set_property("compute-hw", 2)
|
||||
else:
|
||||
nvmultistreamtiler.set_property("compute-hw", 1)
|
||||
sink.set_property("qos",0)
|
||||
|
||||
tracker = Gst.ElementFactory.make("nvtracker", "tracker")
|
||||
if not tracker:
|
||||
sys.stderr.write(" Unable to create tracker \n")
|
||||
tracker.set_property('tracker-width', YOLO_SIZE)
|
||||
tracker.set_property('tracker-height', YOLO_SIZE)
|
||||
# To fix 'gstnvtracker: Unable to acquire a user meta buffer. Try increasing user-meta-pool-size'
|
||||
tracker.set_property('user-meta-pool-size', 128)
|
||||
tracker.set_property('gpu_id', 0)
|
||||
tracker.set_property('ll-lib-file', 'lib/libnvds_nvmultiobjecttracker.so')
|
||||
tracker.set_property('ll-config-file', 'config/config_tracker_NvDCF_perf.yml')
|
||||
|
||||
print("Adding elements to Pipeline \n")
|
||||
pipeline.add(pgie)
|
||||
if nvdslogger:
|
||||
pipeline.add(nvdslogger)
|
||||
pipeline.add(nvmultistreamtiler)
|
||||
pipeline.add(tracker)
|
||||
pipeline.add(nvvidconv)
|
||||
pipeline.add(nvosd)
|
||||
pipeline.add(sink)
|
||||
|
||||
print("Linking elements in the Pipeline \n")
|
||||
nvstreammux.link(queue1)
|
||||
queue1.link(pgie)
|
||||
pgie.link(tracker)
|
||||
tracker.link(queue2)
|
||||
if nvdslogger:
|
||||
queue2.link(nvdslogger)
|
||||
nvdslogger.link(nvmultistreamtiler)
|
||||
else:
|
||||
queue2.link(nvmultistreamtiler)
|
||||
nvmultistreamtiler.link(queue3)
|
||||
queue3.link(nvvidconv)
|
||||
nvvidconv.link(queue4)
|
||||
queue4.link(nvosd)
|
||||
nvosd.link(queue5)
|
||||
|
||||
if display_type == 0:
|
||||
pipeline.add(nvvidconv2)
|
||||
pipeline.add(encoder)
|
||||
pipeline.add(h264parse)
|
||||
pipeline.add(qtmux)
|
||||
|
||||
queue5.link(nvvidconv2)
|
||||
nvvidconv2.link(encoder)
|
||||
encoder.link(h264parse)
|
||||
h264parse.link(qtmux)
|
||||
qtmux.link(sink)
|
||||
else:
|
||||
queue5.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)
|
||||
pgie_src_pad=nvosd.get_static_pad("sink")
|
||||
if not pgie_src_pad:
|
||||
sys.stderr.write(" Unable to get src pad \n")
|
||||
else:
|
||||
if not disable_probe:
|
||||
pgie_src_pad.add_probe(Gst.PadProbeType.BUFFER, pgie_src_pad_buffer_probe, 0)
|
||||
# perf callback function to print fps every 5 sec
|
||||
GLib.timeout_add(5000, perf_data.perf_print_callback)
|
||||
|
||||
# Enable latency measurement via probe if environment variable NVDS_ENABLE_LATENCY_MEASUREMENT=1 is set.
|
||||
# To enable component level latency measurement, please set environment variable
|
||||
# NVDS_ENABLE_COMPONENT_LATENCY_MEASUREMENT=1 in addition to the above.
|
||||
if environ.get('NVDS_ENABLE_LATENCY_MEASUREMENT') == '1':
|
||||
print ("Pipeline Latency Measurement enabled!\nPlease set env var NVDS_ENABLE_COMPONENT_LATENCY_MEASUREMENT=1 for Component Latency Measurement")
|
||||
global measure_latency
|
||||
measure_latency = True
|
||||
|
||||
# List the sources
|
||||
print("Now playing...")
|
||||
for i, source in enumerate(args):
|
||||
print(i, ": ", source)
|
||||
|
||||
print("Starting pipeline \n")
|
||||
# start play back and listed to events
|
||||
pipeline.set_state(Gst.State.PLAYING)
|
||||
try:
|
||||
loop.run()
|
||||
except:
|
||||
pass
|
||||
|
||||
print("总蚕茧数：",count_sc-1)
|
||||
# cleanup
|
||||
print("Exiting app\n")
|
||||
pipeline.set_state(Gst.State.NULL)
|
||||
|
||||
def parse_args():
|
||||
|
||||
parser = argparse.ArgumentParser(prog="deepstream_test_3",
|
||||
description="deepstream-test3 multi stream, multi model inference reference app")
|
||||
parser.add_argument(
|
||||
"-i",
|
||||
"--input",
|
||||
help="Path to input streams",
|
||||
nargs="+",
|
||||
metavar="URIs",
|
||||
default=["a"],
|
||||
required=True,
|
||||
)
|
||||
parser.add_argument(
|
||||
"-c",
|
||||
"--configfile",
|
||||
metavar="config_location.txt",
|
||||
default=None,
|
||||
help="Choose the config-file to be used with specified pgie",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-g",
|
||||
"--pgie",
|
||||
default=None,
|
||||
help="Choose Primary GPU Inference Engine",
|
||||
choices=["nvinfer", "nvinferserver", "nvinferserver-grpc"],
|
||||
)
|
||||
parser.add_argument(
|
||||
"--display_type",
|
||||
type=int,
|
||||
default=0,
|
||||
help="Display type: 0=file, 1=fake"
|
||||
)
|
||||
|
||||
parser.add_argument(
|
||||
"--file-loop",
|
||||
action="store_true",
|
||||
default=False,
|
||||
dest='file_loop',
|
||||
help="Loop the input file sources after EOS",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--disable-probe",
|
||||
action="store_true",
|
||||
default=False,
|
||||
dest='disable_probe',
|
||||
help="Disable the probe function and use nvdslogger for FPS",
|
||||
)
|
||||
parser.add_argument(
|
||||
"-s",
|
||||
"--silent",
|
||||
action="store_true",
|
||||
default=False,
|
||||
dest='silent',
|
||||
help="Disable verbose output",
|
||||
)
|
||||
# Check input arguments
|
||||
if len(sys.argv) == 1:
|
||||
parser.print_help(sys.stderr)
|
||||
sys.exit(1)
|
||||
args = parser.parse_args()
|
||||
|
||||
stream_paths = args.input
|
||||
pgie = args.pgie
|
||||
config = args.configfile
|
||||
disable_probe = args.disable_probe
|
||||
global display_type
|
||||
global silent
|
||||
global file_loop
|
||||
display_type = args.display_type
|
||||
silent = args.silent
|
||||
file_loop = args.file_loop
|
||||
|
||||
if config and not pgie or pgie and not config:
|
||||
sys.stderr.write ("\nEither pgie or configfile is missing. Please specify both! Exiting...\n\n\n\n")
|
||||
parser.print_help()
|
||||
sys.exit(1)
|
||||
if config:
|
||||
config_path = Path(config)
|
||||
if not config_path.is_file():
|
||||
sys.stderr.write ("Specified config-file: %s doesn't exist. Exiting...\n\n" % config)
|
||||
sys.exit(1)
|
||||
|
||||
print(vars(args))
|
||||
return stream_paths, pgie, config, disable_probe
|
||||
|
||||
if __name__ == '__main__':
|
||||
# 此程序支持多个视频流输入，但只为单视频流输入开发
|
||||
|
||||
# 外部输入参数
|
||||
stream_paths, pgie, config, disable_probe = parse_args()
|
||||
|
||||
sys.exit(main(stream_paths, pgie, config, disable_probe))
|
||||
Reference in New Issue
Block a user