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94 changes: 0 additions & 94 deletions Libraries/oneVPL/dpcpp-blur/CMakeLists.txt

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6 changes: 0 additions & 6 deletions Libraries/oneVPL/dpcpp-blur/PreLoad.cmake

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47 changes: 16 additions & 31 deletions Libraries/oneVPL/dpcpp-blur/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,8 @@ oneAPI Video Processing Library to perform a simple video content blur.
| Optimized for | Description
|----------------- | ----------------------------------------
| OS | Ubuntu* 20.04
| Hardware | Intel® Processor Graphics GEN9 or newer
| Hardware | CPU: See [System Requirements](https://software.intel.com/content/www/us/en/develop/articles/oneapi-video-processing-library-system-requirements.html)
| | GPU: Compatible with Intel® oneAPI Video Processing Library(oneVPL) GPU implementation, which can be found at https://github.com/oneapi-src/oneVPL-intel-gpu
| Software | oneAPI Video Processing Library (oneVPL)
| What You Will Learn | How to use oneVPL and DPC++ to convert raw video files into BGRA and blur each frame.
| Time to Complete | 5 minutes
Expand All @@ -31,34 +32,17 @@ directly on VPL output without copies to/from CPU memory.
| Target device | CPU
| Input format | I420
| Output format | BGRA raw video elementary stream
| Output resolution | same as input
| Output resolution | 256 x 192


## License

Code samples are licensed under the MIT license. See
[License.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/License.txt) for details.

Third party program Licenses can be found here: [third-party-programs.txt](https://github.com/oneapi-src/oneAPI-samples/blob/master/third-party-programs.txt)

## Building the `dpcpp-blur` Program

### Using Visual Studio Code* (Optional)

You can use Visual Studio Code (VS Code) extensions to set your environment, create launch configurations,
and browse and download samples.

The basic steps to build and run a sample using VS Code include:
- Download a sample using the extension **Code Sample Browser for Intel oneAPI Toolkits**.
- Configure the oneAPI environment with the extension **Environment Configurator for Intel oneAPI Toolkits**.
- Open a Terminal in VS Code (**Terminal>New Terminal**).
- Run the sample in the VS Code terminal using the instructions below.

To learn more about the extensions and how to configure the oneAPI environment, see
[Using Visual Studio Code with Intel® oneAPI Toolkits](https://software.intel.com/content/www/us/en/develop/documentation/using-vs-code-with-intel-oneapi/top.html).

After learning how to use the extensions for Intel oneAPI Toolkits, return to this readme for instructions on how to build and run a sample.

### On a Linux* System

Perform the following steps:
Expand All @@ -83,45 +67,46 @@ Perform the following steps:

3. Build the program using the following commands:
```
cp $ONEAPI_ROOT/vpl/latest/examples .
cd examples/interop/dpcpp-blur
mkdir build
cd build
cmake ..
cmake --build .
```

4. Run the program using the following command:
4. Run the program with default arguments using the following command:
```
cmake --build . --target run
```



## Running the Sample

### Application Parameters

The instructions given above run the sample executable with these arguments
`-i <sample_dir>/content/cars_128x96.i420 -w 128 -h 96`.
`-i ${CONTENTPATH}/cars_128x96.i420 -w 128 -h 96`.

In Linux, an additional '-hw' parameter will run on GPU if GPU stack components
are found in your environment.

### Example of Output
### Example Output

```
Queue initialized on Intel(R) Core(TM) i5-9400 CPU @ 2.90GHz
Queue initialized on 11th Gen Intel(R) Core(TM) i5-1135G7 @ 2.40GHz
Implementation details:
ApiVersion: 2.4

ApiVersion: 2.5
Implementation type: SW
AccelerationMode via: NA
Path: /opt/intel/oneapi/vpl/2021.4.0/lib/libvplswref64.so.1
AccelerationMode via: NA
DeviceID: 0000
Path: /opt/intel/oneapi/vpl/2021.6.0/lib/libvplswref64.so.1

Processing ../../content/cars_128x96.nv12 -> out.raw
Processing /home/test/intel_innersource/frameworks.media.onevpl.dispatcher/examples/interop/dpcpp-blur/content/cars_128x96.i420 -> out.raw
Processed 60 frames

```

You can find the output file ``out.raw`` in the build directory.
You can find the 256x192 BGRA output file ``out.raw`` in the build directory.

You can display the output with a video player that supports raw streams such as
FFplay. You can use the following command to display the output with FFplay:
Expand Down
1 change: 0 additions & 1 deletion Libraries/oneVPL/dpcpp-blur/content/cars_128x96.i420

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1 change: 0 additions & 1 deletion Libraries/oneVPL/dpcpp-blur/content/cars_128x96.nv12

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30 changes: 13 additions & 17 deletions Libraries/oneVPL/dpcpp-blur/sample.json
Original file line number Diff line number Diff line change
@@ -1,25 +1,21 @@
{
"guid": "8E31124E-3F21-4A8F-A14A-950B7F008480",
"name": "DPCPP Blur",
"categories": ["Toolkit/oneAPI Libraries/oneVPL"],
"description": "Sample that shows how to use Intel(r) oneAPI Video Processing Library (VPL) Data Parallel C++ (DPC++) to convert I420 raw video file in to BGRA and blur each frame",
"dependencies": ["vpl"],
"os": ["linux"],
"languages": [{"cpp":{}}],
"toolchain": ["dpcpp"],
"builder": ["ide", "cmake"],
"targetDevice": ["CPU", "GPU"],
"categories": [ "Toolkit/oneAPI Libraries/oneVPL" ],
"description": "Shows how to use Intel® Video Processing Library (VPL) and Data Parallel C++ (DPC++) to convert I420 raw video file in to BGRA and blur each frame",
"dependencies": [ "vpl" ],
"os": [ "linux" ],
"languages": [ { "cpp": {} } ],
"toolchain": [ "dpcpp" ],
"builder": [ "cmake" ],
"targetDevice": [ "CPU", "GPU" ],
"ciTests": {
"linux": [
{ "id": "builds and runs successfully with CMake",
"env": [ ],
"steps": [
"mkdir build",
"cd build",
"cmake ..",
"cmake --build .",
"cmake --build . --target run"
] }
{
"id": "No build required, readmes only",
"env": [],
"steps": []
}
]
}
}
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