git地址:deepstream_python_apps/apps/runtime_source_add_delete at master · NVIDIA-AI-IOT/deepstream_python_apps · GitHubhttps://github.com/NVIDIA-AI-IOT/deepstream_python_appsdeepstream_python_apps/apps/runtime_source_add_delete at master · NVIDIA-AI-IOT/deepstream_python_apps · GitHub
runtime_source_add_delete
This application demonstrates how to: * Add and delete sources at runtime. * Use a uridecodebin so that any type of input (e.g. RTSP/File), any GStreamer supported container format, and any codec can be used as input. * Configure the stream-muxer to generate a batch of frames and infer on the batch for better resource utilization. * Configure the tracker (referred to as nvtracker in this sample) using config file dstest_tracker_config.txt
add_sources{
#达到最大个数后,开始删source。
if (g_num_sources == MAX_NUM_SOURCES):
GObject.timeout_add_seconds(10, delete_sources, g_source_bin_list)
return False
}
main(){
GObject.timeout_add_seconds(10, add_sources, g_source_bin_list) //每隔开10秒加source.
}
欢迎分享,转载请注明来源:内存溢出
评论列表(0条)