Target of the gamma release

In this version, we have done the following work：

Add some NN modules and Samples.
1. Yolov8 Pose for human posture detection.
2. Yolov8 OBB (oriented bounding box)， can detect the peripheral direction of objects.
3. Yolov8 Segmentation. The detected targets can be identified using masks.
4. Yolov8 Classification. Each target in the detected image can be classified based on confidence level.
5. Vehicle attributes. Can identify trucks, cars, buses, and their respective colors.
6. License plate recognition. It can detect license plates and recognize their contents.
7. Yolov10 Detection. Models for Object Detection.
8. RTMDet. Real-time Models for Object Detection.
Parallel operations in multi-model applications can maximize the utilization of NPU and CPU, ultimately maximizing the processing frame rate of the application.
Implement official and customized partitions.
Arrangement of some folder structs such as tool and algo and so on.
The parameters of nnf_sample are designed in the standard Linux option (-, --) way.

Gamma release resource

Please get the gamma release resource here.

Usage of the gamma release

How to verify Official Demos

You can use the script we provide to start as follows：

   /NNF/release # ./nnf_run.sh
   Usage: ./bin/nnf_nnsample [-m|-s|-a|-h] [-i|-v|-c|option]
   [-m,--model <model>] run a single model
            <model>:yolov5s lightFace age humanAttr ocrDet
                  ocrCls ocrRec yolov8n yolov8nBase yolov8s
                  yolov8sBase vehicle yolov8nCcpd yolov8nClassify yolov8nObb
                  yolov8nPose yolov8nSegment yolov8sDetection yolov8sPose yolov10sDetection
                  rtmdets imageWriter
            example:./bin/nnf_nnsample -m yolov5s
                  ./bin/nnf_nnsample --model humanAttr

   [-s,--sequential <model1,model2,...>] run sequential models
            <models>:yolov5s,humanAttr
                  lightFace,age
                  ocrDet,ocrRec
                  ocrDet,ocrCls,ocrRec
                  yolov8nCcpd,ocrRec
            example:./bin/nnf_nnsample -s yolov5s,humanAttr
                  ./bin/nnf_nnsample --sequential ocrDet,ocrCls,ocrRec

   [-i,--image file] set image file to nn detection.
            <file>: file name or input "." to using inner file.
            example:./bin/nnf_nnsample -s yolov5s,humanAttr -i filename -c testCount
                        ./bin/nnf_nnsample -s yolov5s,humanAttr --image . -c testCount

   [-v,--video file] set video file to nn detection.
            <file>: file name or input "." to using inner file.
            example:./bin/nnf_nnsample -s yolov5s,humanAttr -v filename
                  ./bin/nnf_nnsample -s yolov5s,humanAttr --video .

   [-a,--all] run all model testing

Release folder structure

bin: nnf_nnsample. Prebuild sample programs that can run on the c3v Linux platform.
image: images used for detection.
model: models to be used in the sample program.
include：header file of NN framework SDK.
lib：libraries of NN framework SDK.
souces：example code for using NN framework.
video: Some released video files.
nnf_run.sh：executable script for running sample code.

How to run NN framework sample

Copy the release foler to C3V Linux.

/NNF/release # ls -alh
drwxr-xr-x    9 10989    11400       4.0K Jul  10  2024 .
drwxr-xr-x   10 10989    11400       4.0K Jul  10  2024 ..
drwxr-xr-x    2 10989    11400       4.0K Jul  10  2024 bin
drwxr-xr-x    2 10989    11400       4.0K Jul  10  2024 image
drwxr-xr-x    5 10989    11400       4.0K Jul  10  2024 include
drwxr-xr-x    5 10989    11400       4.0K Jul  10  2024 lib
drwxr-xr-x    2 10989    11400       4.0K Jul  10  2024 model
-rw-r-xr-x    1 10989    11400        398 Jul  10  2024 nnf_run.sh
drwxr-xr-x    5 10989    11400       4.0K Jul  10  2024 sources
drwxr-xr-x    2 10989    11400       4.0K Jul  10  2024 video

Run nnf_run.sh to run the NNF sample.

a. One-time input

./nnf_run.sh -m yolov8n

/NNF/release # ./nnf_run.sh -m yolov8n
yolov8n in
general(box:    0   19  614  619) --> label: 0000, confidence: 0.87
yolov8n out, retVal: 0

b. Read input from the image file

./nnf_run.sh -m yolov8n -i ./image

c. Read inputs from the video file.

./nnf_run.sh -m yolov8n -v ./video/humanCount.mp4

d. Sequential models

./nnf_run.sh -s yolov5s,humanAttr

e. Model inference results save to image

./nnf_run.sh -s yolov8sPose,imageWriter

results will save to the image detected_1883_931_154926538.jpg.

How to build NN framework

Cross-compile for C3V environment.

a. Please use nnf_build.sh for NN framework compiling.

b. All the resouce will installed to release folder.

Copy release folder to the C3V platform.
Setup environment variable.

a. Setting environment variables independently.

b. Run nnf_run.sh will auto set environment variables.

Then, you can run nnf_run.sh for NNF sample.

Models of the gamma release

Model Name	Version or Path
Yolov8 Pose	https://github.com/ultralytics/ultralytics
Yolov8 OBB	https://github.com/ultralytics/ultralytics
Yolov8 Segmentation	https://github.com/ultralytics/ultralytics
Yolov8 Classification	https://github.com/ultralytics/ultralytics
Vehicle attributes	https://bj.bcebos.com/v1/paddledet/models/pipeline/vehicle_attribute_model.zip
License plate recognition	CCPD2020 Yolov8 CCPD detection OCR
Yolov10 Detection	https://github.com/THU-MIG/yolov10
RTMDet	https://github.com/open-mmlab/mmdetection

C3V Documentation

The gamma release of NN Framework