Please provide complete information as applicable to your setup.
• Hardware Platform – GPU
• DeepStream Version – 6.1
• NVIDIA GPU Driver Version – NVIDIA GeForce RTX 2080 Ti
• Triton Version – nvcr.io/nvidia/tritonserver:22.05-py3
HI, I’m using custom sequence preprocess for my own algo.
Triton received data successfully.
But here is many zero, and it’s not works.
LIKE THIS:
values.shape: (1, 9, 1080, 1920)
Here is my preprocess config:
[property]
enable=1
target-unique-ids=1
network-input-shape= 4;9;1080;1920
network-color-format=1
network-input-order=2
tensor-data-type=1
tensor-name=frames
operate-on-gie-id=1
processing-width=1920
processing-height=1080
scaling-pool-memory-type=0
scaling-pool-compute-hw=0
scaling-filter=0
tensor-buf-pool-size=18
custom-lib-path=/opt/nvidia/deepstream/deepstream-6.1/samples/configs/small_object_det/custom_sequence_preprocess/libnvds_custom_sequence_preprocess.so
custom-tensor-preparation-function=CustomSequenceTensorPreparation
[user-configs]
channel-scale-factors=1;1;1
channel-mean-offsets=0;0;0
stride=1
subsample=0
[group-0]
src-ids=0
process-on-roi=1
roi-params-src-0=0;0;1920;1080
inferserver config:
infer_config {
unique_id: 1
gpu_ids: [0]
max_batch_size: 1
backend {
inputs: [{
name: “frames”
dims: [9, 1080, 1920]
}]
outputs: [{
name: “output”
}]
triton {
model_name: “tracker”
version: -1
grpc {
url: “localhost:8501”
enable_cuda_buffer_sharing: true
}
}
}
preprocess {
network_format: IMAGE_FORMAT_RGB
tensor_order: TENSOR_ORDER_NHWC
normalize {
scale_factor: 1.0
channel_offsets: [0, 0, 0]
}
}
postprocess {
other {}
}
extra {
output_buffer_pool_size: 8
copy_input_to_host_buffers: false
}
}
input_control {
process_mode: PROCESS_MODE_FULL_FRAME
operate_on_gie_id: -1
interval: 0
}
output_control {
output_tensor_meta: true
}
PLEASE HELP!!!