Tao_voc/classification: can not classify in Deepstream test2

• Hardware (T4/V100/Xavier/Nano/etc) T4
• Network Type :Classification
• TLT Version :2.0

Dear professor:
I hope use my classification engine in Deepstream. So I follow the step of tao _voc/classification.ipynb and produce a “final_model.etlt”. The Dataset is default set as voc2012, and class number is 20.

I copy “final_model.etlt” to deepstream-test2, and set the SGIE1 loading this engine. But It seems like don’t work.

The Fig.1 is shown the original test-2, the SGIE1 can classify the car color.

After I modify the configure as below:
[property]
gpu-id=0
net-scale-factor=1
offsets=123.67;116.28;103.53

tlt-model-key=ZmFtdW43NmZqOWZkczc5cmZsczFyNGFoODo1MGRlNGE5Ny1mNmYzLTRlZWYtOD**********
tlt-encoded-model=./final_model.etlt
labelfile-path=./SGIElabels.txt

input-dims=3;224;224;0
uff-input-blob-name=input_1

force-implicit-batch-dim=1
batch-size=8

0=FP32 and 1=INT8 mode

network-mode=1
input-object-min-width=10
input-object-min-height=10
process-mode=2
model-color-format=1

gie-unique-id=2
operate-on-gie-id=1
operate-on-class-ids=0
is-classifier=1
output-blob-names=predictions/Softmax
classifier-async-mode=1
classifier-threshold=0.51
process-mode=2
#scaling-filter=0
#scaling-compute-hw=0

I just get the following result

That means the SGIE1 does not work. What is the matter? Could kindly help me?
Thank you very much.

There is no update from you for a period, assuming this is not an issue anymore.
Hence we are closing this topic. If need further support, please open a new one.
Thanks

Please refer to Image Classification — TAO Toolkit 3.22.05 documentation.
Especially for the offset.

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