Low FPS #656
Description
(base) epyc@epyc-R282-Z91-00:~/code/DeepStream-Yolo-master$ deepstream-app -c deepstream_app_config.txt
0:00:00.499745091 112870 0x6141c3d6fa10 INFO nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::deserializeEngineAndBackend() <nvdsinfer_context_impl.cpp:2092> [UID = 1]: deserialized trt engine from :/home/epyc/code/DeepStream-Yolo-master/checkpoint/yolo11n_640_FP16_dy-True.engine
Implicit layer support has been deprecated
INFO: ../nvdsinfer/nvdsinfer_model_builder.cpp:327 [Implicit Engine Info]: layers num: 0
0:00:00.499822051 112870 0x6141c3d6fa10 INFO nvinfer gstnvinfer.cpp:684:gst_nvinfer_logger:<primary_gie> NvDsInferContext[UID 1]: Info from NvDsInferContextImpl::generateBackendContext() <nvdsinfer_context_impl.cpp:2195> [UID = 1]: Use deserialized engine model: /home/epyc/code/DeepStream-Yolo-master/checkpoint/yolo11n_640_FP16_dy-True.engine
0:00:00.516658260 112870 0x6141c3d6fa10 INFO nvinfer gstnvinfer_impl.cpp:343:notifyLoadModelStatus:<primary_gie> [UID 1]: Load new model:/home/epyc/code/DeepStream-Yolo-master/config_infer_primary_yolo11.txt sucessfully
Runtime commands:
h: Print this help
q: Quit
p: Pause
r: Resume
NOTE: To expand a source in the 2D tiled display and view object details, left-click on the source.
To go back to the tiled display, right-click anywhere on the window.
** INFO: <bus_callback:291>: Pipeline ready
Failed to query video capabilities: Invalid argument
** INFO: <bus_callback:277>: Pipeline running
**PERF: FPS 0 (Avg)
**PERF: 9.90 (9.79)
**PERF: 6.87 (8.09)
**PERF: 6.56 (7.55)
**PERF: 7.01 (7.30)
**PERF: 7.19 (7.36)
**PERF: 7.51 (7.40)
**PERF: 7.05 (7.34)
**PERF: 7.84 (7.40)
**PERF: 7.81 (7.45)
my config:
deepstream_app_config.txt:
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=5
[tiled-display]
enable=1
rows=1
columns=1
width=1280
height=720
gpu-id=0
nvbuf-memory-type=0
[source0]
enable=1
type=2
uri=file:///opt/nvidia/deepstream/deepstream/samples/streams/sample_1080p_h264.mp4
num-sources=1
drop-frame-interval=0
gpu-id=0
cudadec-memtype=0
[sink0]
enable=1
type=2
sync=0
gpu-id=0
nvbuf-memory-type=0
[osd]
enable=1
gpu-id=0
border-width=5
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
live-source=1
batch-size=25
batched-push-timeout=40000
width=1280
height=720
enable-padding=0
nvbuf-memory-type=0
[primary-gie]
enable=1
gpu-id=0
gie-unique-id=1
nvbuf-memory-type=0
config-file=config_infer_primary_yolo11.txt
[tests]
file-loop=0
config_infer_primary_yolo11.txt:
[property]
gpu-id=0
net-scale-factor=0.0039215697906911373
model-color-format=0
onnx-file=./checkpoint/yolo11n_640_FP32_dy-True.onnx
model-engine-file=./checkpoint/yolo11n_640_FP16_dy-True.engine
#int8-calib-file=calib.table
labelfile-path=labels.txt
batch-size=1
network-mode=2
num-detected-classes=80
interval=0
gie-unique-id=1
process-mode=1
network-type=0
cluster-mode=2
maintain-aspect-ratio=1
symmetric-padding=1
#workspace-size=2000
parse-bbox-func-name=NvDsInferParseYolo
#parse-bbox-func-name=NvDsInferParseYoloCuda
custom-lib-path=nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so
engine-create-func-name=NvDsInferYoloCudaEngineGet
[class-attrs-all]
nms-iou-threshold=0.45
pre-cluster-threshold=0.25
topk=300
I am using the smallest YOLO model, but the FPS is only in single digits, which is very unreasonable.