Hello,
I am trying to launch the custom YOLO implementation via gst-launch-1.0, so I can develop a PyQt GUI that receives frames from the pipeline. Before beginning on this quest, I need a good pipeline to start out with.
The gstreamer launch is:
gst-launch-1.0 v4l2src device=/dev/video0 ! image/jpeg, width=1280, height=720, framerate=60/1 ! jpegparse ! nvv4l2decoder ! m.sink_0 nvstreammux name=m batch-size=1 width=1280 height=720 gpu-id=0 nvbuf-memory-type=0 ! nvinfer config-file-path=/correct_path_to_config/config_infer_primary_yoloV3_tiny.txt batch-size=1 unique-id=1 ! queue ! nvvideoconvert ! nvdsosd ! nvegltransform ! nveglglessink
The gst-launch-1.0 pipeline above runs, however has the error below, and experiences a terrible framerate (not even 1fps):
gstbasesink.c(2902): gst_base_sink_is_to_late (): /GstPipeline:pipeline0/GstEglGlesSink:eglglesssink0: There may be a timestamping problem, or this computer is too slow
I know that the nvinfer model works, as I’ve run them in the deepstream sdk example for custom YOLO models, however, the frame rate is fine in the example application (24fps avg).
How can I make the gstreamer launch run at the same frame rate as the deepstream sdk?
The deepstream sdk config file, from my understanding, builds the gstreamer pipeline for you. Here is the config file that runs at a nice 24fps on the Nano:
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=5
#gie-kitti-output-dir=streamscl[tiled-display]
enable=1
rows=1
columns=1
width=1280
height=720
gpu-id=0
#(0): nvbuf-mem-default - Default memory allocated, specific to particular platform
#(1): nvbuf-mem-cuda-pinned - Allocate Pinned/Host cuda memory, applicable for Tesla
#(2): nvbuf-mem-cuda-device - Allocate Device cuda memory, applicable for Tesla
#(3): nvbuf-mem-cuda-unified - Allocate Unified cuda memory, applicable for Tesla
#(4): nvbuf-mem-surface-array - Allocate Surface Array memory, applicable for Jetson
nvbuf-memory-type=0[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=1
camera-width=1280
camera-height=720
camera-fps-n=60
camera-v4l2-dev-node=0
#uri=file://…/…/samples/streams/sample_1080p_h264.mp4
num-sources=1
gpu-id=0(0): memtype_device - Memory type Device
(1): memtype_pinned - Memory type Host Pinned
(2): memtype_unified - Memory type Unified
cudadec-memtype=0
[sink0]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File
type=2
sync=0
source-id=0
gpu-id=0
nvbuf-memory-type=0[osd]
enable=1
gpu-id=0
border-width=1
text-size=15
text-color=1;1;1;1;
text-bg-color=0.3;0.3;0.3;1
font=Serif
show-clock=0
clock-x-offset=800
clock-y-offset=820
clock-text-size=12
clock-color=1;0;0;0
nvbuf-memory-type=0[streammux]
gpu-id=0
##Boolean property to inform muxer that sources are live
live-source=0
batch-size=1
##time out in usec, to wait after the first buffer is available
##to push the batch even if the complete batch is not formed
batched-push-timeout=40000Set muxer output width and height
width=1920
height=1080
#enable to maintain aspect ratio wrt source, and allow black borders, works
##along with width, height properties
enable-padding=0
nvbuf-memory-type=0config-file property is mandatory for any gie section.
Other properties are optional and if set will override the properties set in
the infer config file.
[primary-gie]
enable=1
gpu-id=0
#model-engine-file=model_b1_fp32.engine
labelfile-path=labels.txt
batch-size=1
#Required by the app for OSD, not a plugin property
bbox-border-color0=1;0;0;1
bbox-border-color1=0;1;1;1
bbox-border-color2=0;0;1;1
bbox-border-color3=0;1;0;1
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary_yoloV3_tiny.txt[tests]
file-loop=0
Thanks in advance for any help,
Chance