I am using those exact same files.
I’m running the command with
deepstream-app -c deepstream_app_config_fasterRCNN.txt
my deepstream_app_config_fasterRCNN.txt file is
[application]
enable-perf-measurement=1
perf-measurement-interval-sec=1
gie-kitti-output-dir=./
[tiled-display]
enable=0
rows=1
columns=1
width=1280
height=720
gpu-id=0
nvbuf-memory-type=0
[source0]
enable=1
#Type - 1=CameraV4L2 2=URI 3=MultiURI
type=3
num-sources=1
uri=file:/home/user/dev/nvidia/samples/streams/sample_1080p_h264.mp4
gpu-id=0
cudadec-memtype=0
[streammux]
gpu-id=0
batch-size=1
batched-push-timeout=-1
## Set muxer output width and height
width=1920
height=1080
nvbuf-memory-type=0
[sink2]
enable=1
#Type - 1=FakeSink 2=EglSink 3=File 4=RTSPStreaming
type=4
#1=h264 2=h265
codec=1
#encoder type 0=Hardware 1=Software
enc-type=0
sync=1
bitrate=3000000
#H264 Profile - 0=Baseline 2=Main 4=High
#H265 Profile - 0=Main 1=Main10
profile=0
# set below properties in case of RTSPStreaming
rtsp-port=8555
udp-port=5400
[osd]
enable=1
gpu-id=0
border-width=3
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
[primary-gie]
enable=1
gpu-id=0
batch-size=1
gie-unique-id=1
interval=1
config-file=config_infer_primary_frcnn_infer_0_Example.txt
nvbuf-memory-type=0
my config_infer_primary_frcnn_infer_0_Example.txt is the same as you pusted, except for paths.
[property]
gpu-id=0
net-scale-factor=1.0
offsets=103.939;116.779;123.68
model-color-format=1
labelfile-path=/home/user/dev/nvidia/proyectos/ejemplos/deepstream_tlt_apps/configs/frcnn_tlt/frcnn_labels.txt
tlt-encoded-model=/home/user/dev/nvidia/proyectos/ejemplos/deepstream_tlt_apps/models/frcnn/faster_rcnn_resnet18.etlt
tlt-model-key=nvidia_tlt
model-engine-file=/home/user/dev/nvidia/proyectos/ejemplos/deepstream_tlt_apps/models/frcnn/faster_rcnn_resnet18.etlt_b1_gpu0_fp16.engine
infer-dims=3;544;960
uff-input-order=0
uff-input-blob-name=input_image
batch-size=1
## 0=FP32, 1=INT8, 2=FP16 mode
network-mode=2
num-detected-classes=5
interval=0
gie-unique-id=1
is-classifier=0
#network-type=0
output-blob-names=NMS
cluster-mode=2
parse-bbox-func-name=NvDsInferParseCustomNMSTLT
custom-lib-path=/home/user/dev/nvidia/proyectos/ejemplos/deepstream_tlt_apps/post_processor/libnvds_infercustomparser_tlt.so
[class-attrs-all]
pre-cluster-threshold=0.6
roi-top-offset=0
roi-bottom-offset=0
detected-min-w=0
detected-min-h=0
detected-max-w=0
detected-max-h=0
and finnaly, frcnn_labels.txt is
Bicycle
Car
Person
Roadsign
background
I double checked every path with ls and more commands.
The sample video is one of the provided by deepstream.