Gsteramer使用mppvideodec硬解码依旧延迟过大 - Firefly开源社区

import gi
gi.require_version('Gst', '1.0')
from gi.repository import Gst, GObject, GLib
# 初始化GStreamer
Gst.init(None)
loop = GLib.MainLoop()
pipeline = Gst.parse_launch("rtspsrc location=rtsp://192.168.0.133:554/test ! rtph264depay ! h264parse ! mppvideodec ! videorate ! video/x-raw,framerate=60/1 ! videoscale ! videoconvert ! video/x-raw,width=1280,height=720 ! autovideosink sync=false")
# 设置管道状态为播放
pipeline.set_state(Gst.State.PLAYING)
# 开始主循环
try:
loop.run()
except KeyboardInterrupt:
# 捕获键盘中断事件，停止管道并退出
pipeline.set_state(Gst.State.NULL)
loop.quit()

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import heartrate; heartrate.trace(browser=True)
import gi
import cv2
import numpy as np
from gi.repository import Gst
gi.require_version('Gst', '1.0')
# 初始化GStreamer
Gst.init(None)
import time # 导入time模块
def gst_to_opencv(sample):
start_time = time.time() # 获取函数开始的时间
buf = sample.get_buffer()
caps = sample.get_caps()
print("图像数据格式:", caps.to_string())
array = np.ndarray(
(caps.get_structure(0).get_value('height'),
caps.get_structure(0).get_value('width'),
3),
buffer=buf.extract_dup(0, buf.get_size()),
dtype=np.uint8)
end_time = time.time() # 获取函数结束的时间
print("gst_to_opencv耗时: {:.5f}秒".format(end_time - start_time)) # 打印函数耗时
return array
def new_sample(sink, data):
sample = sink.emit('pull-sample')
start_time = time.time() # 获取OpenCV处理开始的时间
frame = gst_to_opencv(sample)
cv2.imshow('Live Video', frame)
cv2.waitKey(1)
end_time = time.time() # 获取显示结束的时间
print("OpenCV显示耗时: {:.5f}秒".format(end_time - start_time)) # 打印OpenCV处理+显示耗时
return Gst.FlowReturn.OK
# 设置GStreamer管道
pipeline = Gst.parse_launch('rtspsrc location=rtsp://192.168.0.133:554/test ! rtph264depay ! h264parse ! mppvideodec ! videorate ! video/x-raw,framerate=60/1 ! videoscale ! videoconvert ! video/x-raw,format=BGR,width=1280,height=720 ! appsink emit-signals=True name=mysink')
sink = pipeline.get_by_name('mysink')
sink.set_property('sync', False)
sink.connect('new-sample', new_sample, None)
pipeline.set_state(Gst.State.PLAYING)
try:
while True:
pass # 循环运行，直到用户关闭窗口
except KeyboardInterrupt:
print("Interrupted by user")
cv2.destroyAllWindows()
pipeline.set_state(Gst.State.NULL)

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