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Clone the TensorFlow Object Detection API from GitHub and set the API's base\ndirectory as an environment variable for later use:\n    ```bash\n    $ cd \u003cdirectory_of_your_choice\u003e\n    $ git clone git@github.com:tensorflow/models.git\n    $ cd models\n    $ export TFOD=`pwd`\n    ```\n2. Create a new Python environment (or activate an existing Python environment).\nIn this example we'll use an Anaconda environment:\n    ```bash\n    $ conda create -n tltod python=3 --yes\n    $ conda activate tltod\n    ```\n3. Install TensorFlow and other necessary packages:\n    ```bash\n    $ pip install tensorflow\n    $ pip install Cython\n    $ pip install contextlib2\n    $ pip install pillow\n    $ pip install lxml\n    $ pip install jupyter\n    $ pip install matplotlib\n    ```\n4. Compile the Protobuf libraries:\n    ```bash\n    $ cd ${TFOD}/research\n    $ protoc object_detection/protos/*.proto --python_out=.\n    ```\n5. Add the API's `research` and `research/slim` directories to the `PYTHONPATH` variable:\n    ```bash\n    $ cd ${TFOD}/research\n    $ export PYTHONPATH=`pwd`:`pwd`/slim\n    ```\n6. Test the installation:\n    ```bash\n    $ python object_detection/builders/model_builder_test.py\n    ```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmonocongo%2Fvod_convert","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmonocongo%2Fvod_convert","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmonocongo%2Fvod_convert/lists"}