使用 Orangepi5b_1.0.4_ubuntu_jammy_desktop_xfce_linux5.10.110 镜像, 自带了python3 和docker, 使用默认的即可
cd /data/github_codes/
wget https://bootstrap.pypa.io/get-pip.py
python get-pip.py
python -m pip install requests -i https://pypi.tuna.tsinghua.edu.cn/simple/
python -m pip install tritonclient[all] -i https://pypi.tuna.tsinghua.edu.cn/simple/
python -m pip install numpy opencv-python -i https://pypi.tuna.tsinghua.edu.cn/simple/

// 使用我本地的环境目录
cd /data/github_codes/server
./build/opt/tritonserver/bin/tritonserver  --model-repository /data/github_codes/server/build/rknn/examples/models --backend-directory /data/github_codes/server/build/opt/tritonserver/backends/

# 需要预先在python环境安装 tritonclient
cd /data/github_codes/server/build/rknn/examples/yolov5
python test_yolov5.py

--> Running model
0: infer 0
class: person, score: 0.819098949432373
box coordinate left,top,right,down: [114.69233334064484, 235.684387922287, 212.63444888591766, 527.1685173511505]
class: person, score: 0.8149696588516235
box coordinate left,top,right,down: [210.97113871574402, 242.16578316688538, 284.33705830574036, 509.1424443721771]
class: person, score: 0.7903112769126892
box coordinate left,top,right,down: [479.5874242782593, 235.37401449680328, 561.1043481826782, 520.7360318899155]
class: person, score: 0.4049600064754486
box coordinate left,top,right,down: [78.8878903388977, 338.7200300693512, 122.68799161911011, 520.08789229393]
class: bus , score: 0.6933198571205139
box coordinate left,top,right,down: [99.32104778289795, 141.9212429523468, 557.3707246780396, 445.96871066093445]

# 可以通过修改/data/github_codes/server/build/rknn/examples/models/yolov5/config.pbtxt
# 配置模型实例个数和模型加载的npu核id
# 注：目前，暂时不支持模型core_mask按RKNN_NPU_CORE_0_1和RKNN_NPU_CORE_0_1_2进行加载

cd /data/github_codes/server/build/rknn/examples/single_input
python test_single_input.py

--> Running model
0: infer 0
Shih-Tzu:0.984375
Pekinese:0.0078125
Lhasa:0.00390625

cd /data/github_codes/server/build/rknn/examples/ensemble_mobilenet
python test_ensemble_mobilenet.py --image ../single_input/dog_224x224.jpg --label_file ../single_input/labels.txt

# Result is class: Shih-Tzu