When I use the ResNet18.onnx model (which can be divided into 10 categories in total) for level 2 inference on DeepStream, I can only detect one category (black) and cannot detect other categories .Level 1 reasoning is YOLOV8.Here is my configuration file
[property]
gpu-id=0
labelfile-path=/home/nvidia/sby/resnet18_model_onnx/classes.txt
onnx-file=/home/nvidia/sby/resnet18_model_onnx/best_model_1016.onnx
#model-engine-file=/home/nvidia/sby/resnet18_model_onnx/best_model_1016.onnx_b16_gpu0_fp16.engine
net-scale-factor=0.01742919
offsets=114.75;114.75;114.75
network-type=1
#model-file=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Secondary_CarColor/resnet18.caffemodel
#proto-file=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Secondary_CarColor/resnet18.prototxt
#int8-calib-file=/opt/nvidia/deepstream/deepstream-6.0/samples/models/Secondary_CarColor/cal_trt.bin
#model-engine-file=/root/videoBox/common/color_classification/resnet18.caffemodel_b16_gpu0_fp16.engine
#mean-file=/root/videoBox/common/color_classification/mean.ppm
#labelfile-path=/root/videoBox/common/color_classification/labels.txt
#int8-calib-file=/root/videoBox/common/color_classification/cal_trt.bin
#force-implicit-batch-dim=1
batch-size=16
0=FP32 and 1=INT8 mode
network-mode=1
input-object-min-width=8
input-object-min-height=8
process-mode=2
model-color-format=1
gpu-id=0
gie-unique-id=4
operate-on-gie-id=2
operate-on-class-ids=2;3;5;7;
is-classifier=1
num-detected-classes=10
#uff-input-blob-name=input_1
output-blob-names=predictions/Softmax
classifier-async-mode=1
classifier-threshold=0.51
classifier-threshold=0.51
process-mode=2
#scaling-filter=0
#scaling-compute-hw=0
#[class-attrs-all]
pre-cluster-threshold=0.2
topk=20
nms-iou-threshold=0.5