# How to: receive and use the 2D RGB image

Receiving RGB data with ifm3d is done similarly as 3D data: the core objects have to be instantiated, and a frame has to be retrieved (see full code below). 
The important part is how to access the RGB image and how to decode it for further use.

## Access the data
The RGB image is stored in JPEG format and can be retrieved as follows:
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::::{group-tab} Python
:::python
jpeg = frame.get_buffer(buffer_id.JPEG_IMAGE)
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::::{group-tab} C++
:::cpp
auto jpeg = frame->GetBuffer(ifm3d::buffer_id::JPEG_IMAGE);
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## Decode the data
Once accessed, the RGB image has to be decoded. We use OpenCV in this example:
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::::{group-tab} Python
:::python
rgb_decode = cv2.imdecode(jpeg, cv2.IMREAD_UNCHANGED)
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::::{group-tab} C++
:::cpp
auto rgb_decode = cv::imdecode(jpeg, cv::IMREAD_UNCHANGED);
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## Display (optional)
The decoded image can then be displayed, for instance with OpenCV. 
> Note that in c++, the image first has to be converted to a cv::Mat.
> Follow the full example for the conversion to cv::Mat with or without copy.
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::::{group-tab} Python
:::python
cv2.startWindowThread()
cv2.namedWindow("2D image", cv2.WINDOW_NORMAL)
# get frame
# ...
... 
cv2.imshow('RGB image', rgb_decode)
cv2.waitKey(0)
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::::{group-tab} C++
:::cpp
cv::startWindowThread();
cv2.namedWindow("RGB image", cv2::WINDOW_NORMAL)

cv::imshow("RGB image", rgb_decode);
cv::waitKey(0);
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## The full example
:::::{tabs}
::::{group-tab} Python
:::{literalinclude} 2d_data.py
:language: python
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::::{group-tab} C++
:::{literalinclude} 2d_data.cpp
:language: cpp
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