~~tags>VIM4 NPU~~
**Doc for version ddk-3.4.7.7**
====== NPU Applications ======
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Only **New VIM4** supports NPU, you can check the version of your VIM4 here: [[products:sbc:vim4:configurations:identify-version|]]
===== Linux =====
Only supports OpenCV4.
==== Get source code ====
You need to download the source code to your VIM4 board and compile on it.
Clone the NPU demo applications to somewhere, e.g. ''~/workspace'':
```shell
$ mkdir ~/workspace
$ cd ~/workspace
$ git clone https://github.com/khadas/vim4_npu_applications
$ cd vim4_npu_applications
$ ls
densenet_ctc facenet face_recognition face_recognition_cap retinaface retinaface_cap vgg16 yolov3 yolov3_cap yolov7_tiny yolov7_tiny_cap yolov8n yolov8n_cap
```
* ''densenet_ctc'', ''facenet'', ''retinaface'', ''yolov3'', ''yolov7_tiny'', ''yolov8n'' - Different demo for VIM4 NPU.
Please use convert tool version tag ddk-3.4.7.7 or higher.
==== Install dependences ====
```shell
$ sudo apt update
$ sudo apt install libopencv-dev python3-opencv cmake
```
==== Compile ====
Take ''yolov3'' as an example, other demos are the same.
```shell
$ cd yolov3
$ mkdir build && cd build
$ cmake ..
$ make
```
==== Run ====
=== Yolov3 ===
The demos of the Yolo series only support running under the desktop environment.
Before running, please compile the source code. The compilation method is same as ''Mobilenet V2''.
Detect picture:
```shell
$ cd yolov3/build
$ ./yolov3 -p ../data/1080p.bmp -m ../data/det_yolov3_int8.adla
```
{{:products:sbc:vim4:npu:vim4-yolov3-output.webp?1000|}}
Detection with camera:
```shell
$ cd yolov3_cap/build
$ ./yolov3_cap -m ../data/det_yolov3_int8.adla -d X -w 1920 -h 1080
```
**x**: the number for you camera device. such as ''/dev/video0'', ''x'' is ''0''.
===== Android =====
WIP: