# SAM-ONNX-AX650-CPP

**Repository Path**: axera-opensource/SAM-ONNX-AX650-CPP

## Basic Information

- **Project Name**: SAM-ONNX-AX650-CPP
- **Description**: No description available
- **Primary Language**: C++
- **License**: BSD-3-Clause
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-10-16
- **Last Updated**: 2024-05-31

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Inpaint Anything

https://github.com/ZHEQIUSHUI/SAM-ONNX-AX650-CPP/assets/46700201/82b35088-7e9c-46b8-980f-bc9a3bc9996c

## Build
```bash
mkdir build
cd build
```
if x86 onnxruntime
```bash
cmake -DONNXRUNTIME_DIR=${onnxruntime_dir} -DOpenCV_DIR=${opencv_cmake_file_dir} ..
```
else if ax650
```bash
cmake -DONNXRUNTIME_DIR=${onnxruntime_dir} -DOpenCV_DIR=${opencv_cmake_file_dir} -DBSP_MSP_DIR=${msp_out_dir} -DBUILD_WITH_AX650=ON ..
```
```bash
make -j4
```

### Build with QT

```bash
cd qtproj
mkdir build
```
build for x86 (for example qt5.14.2,ubuntu 20.04,you need to download opencv and onnxruntime)
```bash
cmake -DONNXRUNTIME_DIR=${onnxruntime_dir} -DOpenCV_DIR=${opencv_cmake_file_dir} -DQt5_DIR=${qt5_dir}/5.14.2/gcc_64/lib/cmake/Qt5  ../SAMQT/
```
build for AX650 on board(爱芯派pro，you need to download opencv onnxruntime in this repos releases)
```bash
apt install cmake qt6-base-dev qtcreator
cmake -DONNXRUNTIME_DIR=${onnxruntime_dir} -DOpenCV_DIR=${opencv_cmake_file_dir} -DBSP_MSP_DIR=${msp_out_dir} -DBUILD_WITH_AX650=ON ../SAMQT/
```
```
make -j4
```
## Usage

![](test.jpg)

### Segment Anything
```
/opt/test/sam # ./main -e ax_models/sam-encoder.axmodel -d ax_models/sam_vit_b_01ec64_decoder.onnx -i test.jpg
Engine creating handle is done.
Engine creating context is done.
Engine get io info is done.
Engine alloc io is done.
[I][                            init][ 233]: BGR MODEL
Encoder Inference Cost time : 0.737574s
Decoder Inference Cost time : 0.448962s
0.96
0.95
0.96
0.86
Decoder Inference Cost time : 0.438249s
0.98
1.00
0.98
0.91
```
<img src="results/result_0.jpg" height="135" /><img src="results/result_1.jpg" height="135" /><img src="results/result_2.jpg" height="135" /><img src="results/result_3.jpg" height="135" />

<img src="results/rect_result_0.jpg" height="135" /><img src="results/rect_result_1.jpg" height="135" /><img src="results/rect_result_2.jpg" height="135" /><img src="results/rect_result_3.jpg" height="135" />


### Inpaint
```
/opt/test/sam # ./main_inpaint -m big-lama-regular.axmodel  -i test.jpg --mask result_1
.jpg
image 1920x1282
mask 1920x1282
Engine creating handle is done.
Engine creating context is done.
Engine get io info is done.
Engine alloc io is done.
[I][                            init][ 275]: RGB MODEL
Inpaint Inference Cost time : 0.582908s
```
<img src="images/test.jpg"  height="180"/><img src="results/result_1.jpg" height="180" /><img src="results/inpainted.jpg" height="180" />

## Reference
[segment-anything](https://github.com/facebookresearch/segment-anything)\
[MobileSAM](https://github.com/ChaoningZhang/MobileSAM)\
[lama](https://github.com/advimman/lama)\
[SegmentAnything-OnnxRunner](https://github.com/OroChippw/SegmentAnything-OnnxRunner)