
# EasyDeepLearningInferenceLive_FakeCameraFFmpeg_Console

This code sample sample shows how to use Open eVision in a live application to do inspection with a Deep
Learning tool. It is mostly aimed at being a demonstration of Open eVision on embedded platforms like smart
cameras.

This code sample is available in many different variants. The one you are currently reading is using:

* A console displayer that will output the deep learning inspection result on the command line.
* A fake virtual camera that will play a user-specified video with the FFmpeg libraries.

Please note that the current sample was distributed along with other similar samples providing other connectivity
possibilities. Please consult those other samples if the current one is not appropriate for your use case.

## Dependencies

### Open eVision

This sample depends on Open eVision. Please install it in a version suitable for your platform.

All Open eVision releases are available at this address: https://www.euresys.com/en/Support/Download-area

### GCC

This sample necessitates a GCC building solution able to compile C++ 17.

To install it on a Debian-based operating system use this command:

```
sudo apt install build-essential
```

### CMake

This sample necessitates CMake >= 3.1.0 .

To install it on a Debian-based operating system use this command:

```
sudo apt install cmake
```

## Fake camera using a video played with FFmpeg libraries

This sample necessitates the following FFmpeg libraries: libavformat, libavutil, libavcodec, and libswscale.

To install these libraries on a Debian-based system (NVIDIA Jetson, Raspbian OS, Ubuntu, etc.), use the following
command:

```
sudo apt install libavcodec-dev libavutil-dev libavformat-dev libswscale-dev
```


## Using a deep Learning tool

This project can open any Deep Learning tool (EasyClassify, EasySegment, EasyLocate) exported from Deep Learning Studio.

In the Deep Learning Additional Resources, you can find `model.edltool` files for each dataset that can be used with this sample.


## Compiling this sample

Use the following commands in order to compile your project:

```bash
mkdir build
cd build
cmake ..
make -j2
```

Alternatively, you could build the sample by using Qt Creator. To do so, open the CMakeLists.txt file in Qt Creator.

## Using this sample

When launched this sample will capture data from the camera and output the result of the deep learning inspection
in the command line.

This sample is intended to be run on low ressources computers without a graphical interface and does not provide video
confirmation. If you want to have a video confirmation you should use one of the Qt samples distributed along with the
current sample instead.

