YOLOv8

Environment Setup

info

Follow RKNN Installation to set up the environment.

Follow RKNN Model Zoo to download the example files.

Model Download

Download the ONNX model file.

X64 Linux PC

cd rknn_model_zoo/examples/yolov8/model/
bash download_model.sh

Model Conversion

Select the target platform.

rk3588

X64 Linux PC

export TARGET_PLATFORM=rk3588

rk356x

X64 Linux PC

export TARGET_PLATFORM=rk356x

rk3576

X64 Linux PC

export TARGET_PLATFORM=rk3576

Convert the ONNX model to an RKNN model.

X64 Linux PC

cd ../python/
python convert.py ../model/yolov8n.onnx ${TARGET_PLATFORM}

C API

Build the Example

Go to the rknn_model_zoo directory and run build-linux.sh to build.

X64 Linux PC

cd ../../..
bash build-linux.sh -t ${TARGET_PLATFORM} -a aarch64 -d yolov8

Sync Files to the Device

Copy the built demo directory under the install folder to the device.

X64 Linux PC

cd install/${TARGET_PLATFORM}_linux_aarch64/
scp -r rknn_yolov8_demo/ user@your_device_ip:target_directory

Run the Example

Export the runtime libraries to the environment variable.

Device

cd rknn_yolov8_demo/
export LD_LIBRARY_PATH=./lib

Run the example.

Device

./rknn_yolov8_demo model/yolov8.rknn model/bus.jpg

$ ./rknn_yolov8_demo model/yolov8.rknn model/bus.jpg
load label ./model/coco_80_labels_list.txt
model input num: 1, output num: 9
input tensors:
  index=0, name=images, n_dims=4, dims=[1, 640, 640, 3], n_elems=1228800, size=1228800, fmt=NHWC, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.003922
output tensors:
  index=0, name=318, n_dims=4, dims=[1, 64, 80, 80], n_elems=409600, size=409600, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-58, scale=0.117659
  index=1, name=onnx::ReduceSum_326, n_dims=4, dims=[1, 80, 80, 80], n_elems=512000, size=512000, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.003104
  index=2, name=331, n_dims=4, dims=[1, 1, 80, 80], n_elems=6400, size=6400, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.003173
  index=3, name=338, n_dims=4, dims=[1, 64, 40, 40], n_elems=102400, size=102400, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-45, scale=0.093747
  index=4, name=onnx::ReduceSum_346, n_dims=4, dims=[1, 80, 40, 40], n_elems=128000, size=128000, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.003594
  index=5, name=350, n_dims=4, dims=[1, 1, 40, 40], n_elems=1600, size=1600, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.003627
  index=6, name=357, n_dims=4, dims=[1, 64, 20, 20], n_elems=25600, size=25600, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-34, scale=0.083036
  index=7, name=onnx::ReduceSum_365, n_dims=4, dims=[1, 80, 20, 20], n_elems=32000, size=32000, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.003874
  index=8, name=369, n_dims=4, dims=[1, 1, 20, 20], n_elems=400, size=400, fmt=NCHW, type=INT8, qnt_type=AFFINE, zp=-128, scale=0.003922
model is NHWC input fmt
model input height=640, width=640, channel=3
origin size=640x640 crop size=640x640
input image: 640 x 640, subsampling: 4:2:0, colorspace: YCbCr, orientation: 1
scale=1.000000 dst_box=(0 0 639 639) allow_slight_change=1 _left_offset=0 _top_offset=0 padding_w=0 padding_h=0
rga_api version 1.10.1_[0]
rknn_run
person @ (211 241 282 506) 0.864
bus @ (96 136 549 449) 0.864
person @ (109 235 225 535) 0.860
person @ (477 226 560 522) 0.848
person @ (79 327 116 513) 0.306
write_image path: out.png width=640 height=640 channel=3 data=0x32a58800

Results

Python API

Activate the virtual environment

Device

conda activate rknn

Run the Example

Copy the related files to the device and run the following commands.

Device

python yolov8.py --model_path ./model/yolov8.rknn --target ${TARGET_PLATFORM} --img_folder ./model --img_save

$ python yolov8.py --model_path ./model/yolov8.rknn --target rk3588 --img_folder ./model --img_save
/home/radxa/miniforge3/envs/rknn/lib/python3.12/site-packages/rknn/api/rknn.py:51: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.
  self.rknn_base = RKNNBase(cur_path, verbose)
I rknn-toolkit2 version: 2.3.2
--> Init runtime environment
I target set by user is: rk3588
done
Model-./model/yolov8.rknn is rknn model, starting val
W inference: The 'data_format' is not set, and its default value is 'nhwc'!


IMG: bus.jpg
person @ (211 241 282 506) 0.864
person @ (109 235 225 535) 0.860
person @ (477 226 560 522) 0.848
person @ (79 327 116 513) 0.306
bus  @ (96 136 549 449) 0.864
Detection result save to ./result/bus.jpg

Results