Mission 
=======================


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    <div style="background: #ffe5b4" class="admonition note custom">
        <p style="background: #ffbf00" class="admonition-title">
            Project Name: GoogleNet Image Identification System
        </p>
        <div class="line-block">
            <div class="line"><strong>-</strong> This mission is an <strong>individual project</strong></div>
            <div class="line"><strong>-</strong> Identify the different images stored within the system using the AlexNet Image Identification System.</div>
            <div class="line"><strong>-</strong> Within your individual computers, execute the following mission.</div>
        </div>
    </div>



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    <div style="position: relative; color: black; height: 0; overflow: hidden; max-width: 100%; height: auto;">
        <h2>Overall Description:</h2>
    </div>


Let us try to identify different objects with our GoogleNet image idenfitication system. 

For this mission, you will be tasked to see the image identification system work 
on different pictures. We will work with the with the image identification program
directly from our jupyter notebook, hence we will not be using our shell programs. 



Open the gogolenet_mission python notebook:

-   02_1-2.googlenet_mission.ipynb
-   | Running the cell code
    | `Ctrl + Enter`

.. thumbnail:: /_images/ai_image_recognition/google_mission.png



-   This mission will use python library called ``Image``. This allows us to view images within our jupyter notebook environment. 

    .. code-block:: python

        from IPython.display import Image

-   For our jupyter notebook to run, we must set up correct file paths.

    .. code-block:: python 

        # Evnironment variables
        %env PROGRAM_PATH=/home/zeta/jetson-inference/build/aarch64/bin
        %env INPUT_PATH=/home/zeta/jetson-inference/build/aarch64/bin/images
        %env OUTPUT_PATH=/home/zeta/jetson-inference/build/aarch64/bin/images/test/result_1.jpg

        # Python variables
        program_path = '/home/zeta/jetson-inference/build/aarch64/bin/'
        input_path = '/home/zeta/jetson-inference/build/aarch64/bin/images/'
        output_path = '/home/zeta/jetson-inference/build/aarch64/bin/images/test/result_1.jpg'


-   Check all the available images in our system

    .. code-block:: python

        !ls $INPUT_PATH | grep \.jpg$ 

-   Choose one of them and change *CHANGEME* string with the chosen picture name.

    .. code-block:: python 

        # Enter the image file name in image_name variable
        image_name = 'CHANGEME' #example: orange_0.jpg
        %env IMG_NAME = $image_name

-   Check if the chosen picture is valid

    .. code-block:: python

        Image(filename=input_path+image_name) 


-   Run the program on the specified picture

    .. code-block:: python

        !python3 $PROGRAM_PATH/imagenet.py --network=googlenet $INPUT_PATH/$IMG_NAME $OUTPUT_PATH

-   Display the result

    .. code-block:: python

        Image(filename=output_path)