Hi,
We are done classification training on 2080Ti and generate etlt and trt when we test result of generated trt ,It was give above 80% good result on video on 2080Ti but ,We convert etlt file in engine file via tlt-converter on xavier NX it give bad result on same video ,Please help us to resolve this problem and find the reason why result is bad on xavier NX below is my some configuration
Deepstream 5.0
Training Env : 2080Ti , TLT container nvcr.io/nvidia/tlt-streamanalytics:v2.0_py3
Testing Env : jetson Xavier NX, jetpack 4.4
command using for tlt convet (tlt_7.1) on jetson xavier NX:
./tlt-converter -k 'abcd1234' -c age_classification.bin -d 3,224,224 -o predictions/Softmax -e ./age_classification_int8.engine -i nchw -m 64 -b 64 -t int8 ./age_classification.etlt
testing via deepstream 5.0 on both Env (2080Ti and xavier NX) and same config file using below is details of config file,
[property]
gpu-id=0
net-scale-factor=1
model-engine-file=./Model/age_classification_int8.engine (For Xavier NX)
#model-engine-file=./Model/age_classification.trt (for 2080 TI)
labelfile-path=./Model/age_classification.txt
batch-size=1
network-mode=1
input-object-min-width=0
input-object-min-height=0
process-mode=2
model-color-format=1
gpu-id=0
gie-unique-id=4
operate-on-gie-id=1
operate-on-class-ids=0
is-classifier=1
output-blob-names=predictions/Softmax
classifier-async-mode=0
classifier-threshold=0.50