• Hardware Platform GeForce RTX 2080 Ti
• DeepStream Version 6.2
• Issue Type questions
I tried to use two yolo modes to detect people and their head by using nvinferserver，one yolo model detect person as pgie, another one detect head as sgie, sgie based on pgie, i wana sgie detect cropped roi from pgie, pgie can detect correctly, but sgie cant detect correctly. When i chage the process_mode to 1 in sgie, sgie can detect correctly, so i think my preprocess in sgie may wrong.
Blew are my config files:
pgie:
infer_config {
unique_id: 1
gpu_ids: [0]
max_batch_size: 1
backend {
inputs: [ {
#name: "input"
name: "images"
}]
outputs: [
#{name: "boxes"},
#{name: "scores"},
#{name: "classes"}
{name: "output"}
#{name: "onnx::Sigmoid_401" },
#{name: "onnx::Sigmoid_467" },
#{name: "onnx::Sigmoid_533" }
]
triton {
model_name: "Meeting_Person"
version: -1
model_repo {
root: "../../../../samples/triton_model_repo"
strict_model_config: false
}
}
}
preprocess {
network_format: IMAGE_FORMAT_RGB
tensor_order: TENSOR_ORDER_LINEAR
tensor_name: "images"
maintain_aspect_ratio: 1
symmetric_padding: 1
normalize {
scale_factor: 0.0039215697906911373
#scale_factor: 1.0
channel_offsets: [0,0,0]
}
}
postprocess {
labelfile_path: "./labels.txt"
detection {
num_detected_classes: 1
#custom_parse_bbox_func: "NvDsInferParse"
custom_parse_bbox_func: "NvDsInferParseCustomYoloV5"
nms {
confidence_threshold: 0.5
iou_threshold: 0.3
topk : 200
}
}
}
custom_lib {
path: "./old_lib/libnvdsinfer_custom_impl_Yolo.so"
#path: "./nvdsinfer_custom_impl_Yolo/libnvdsinfer_custom_impl_Yolo.so"
}
extra {
copy_input_to_host_buffers: false
output_buffer_pool_size: 2
}
}
input_control {
process_mode: PROCESS_MODE_FULL_FRAME
interval: 0
}
sgie:
infer_config {
unique_id: 2
gpu_ids: [0]
max_batch_size: 1
backend {
inputs: [
{name: "images"}
]
outputs: [
{name: "output"}
]
triton {
model_name: "Meeting_Head"
version: -1
model_repo {
root: "../../../../samples/triton_model_repo"
strict_model_config: false
}
}
}
preprocess {
network_format: IMAGE_FORMAT_RGB
tensor_order: TENSOR_ORDER_LINEAR
#frame_scaling_hw: FRAME_SCALING_HW_DEFAULT
#frame_scaling_filter: 1
#tensor_name: "images"
maintain_aspect_ratio: 1
symmetric_padding: 1
normalize {
scale_factor: 0.0039215697906911373
#scale_factor: 1.0
channel_offsets: [0,0,0]
}
}
postprocess {
labelfile_path: "./labels_call.txt"
detection {
num_detected_classes: 1
custom_parse_bbox_func: "NvDsInferParseCustomYoloV5"
nms {
confidence_threshold: 0.5
iou_threshold: 0.3
topk : 200
}
}
}
custom_lib {
path: "./old_lib/libnvdsinfer_custom_impl_Yolo.so"
}
extra {
copy_input_to_host_buffers: false
output_buffer_pool_size: 2
}
}
input_control {
#process_mode: PROCESS_MODE_FULL_FRAME
interval: 0
process_mode: PROCESS_MODE_CLIP_OBJECTS
operate_on_gie_id: 1
operate_on_class_ids: [0]
#async_mode: true
}