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2. Create a new and clean folder called e.g. `ml` somewhere, and inside, clone `setup_common_lib` and this GitHub repository (here with SSH keys):
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Note: Currently, the repository `setup_common_lib` lives inside restricted BSH SDD.
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3. Inside `ml/tf_vision/ansible/` setup your machine by running Ansible:
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3. Inside `ml/tf_vision/config/` the YAML file `config.local.sample.yml` contains the default configuration on how to provision your machine.
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This includes e.g. enabling or disabling TensorFlow GPU acceleration, TensorFlow version to use, OpenCV version to use, Python version to use.
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In order to overwrite default values, create a local copy `cp config.local.sample.yml config.local.yml` and modify values inside `config.local.yml` only.
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4. Inside `ml/tf_vision/ansible/` setup your machine by running Ansible:
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```
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ansible-playbook -i hosts -v local.yml -K
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# Run
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Inside `ml/tf_vision/` simply run:
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1. Inside `ml/tf_vision/config/` the YAML file `config.obj_detect.sample.yml` contains the default configuration to run.
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This includes e.g. the model to use for object detection, the source for the video stream to analyze upon, and if certain components (like the visualizer or the speech synthesis) should be enabled.
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```
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# Python 2.7
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python obj_detect.py
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# Python 3.5
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python3 obj_detect.py
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```
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In order to overwrite default values, create a local copy `cp config.obj_detect.sample.yml config.obj_detect.yml` and modify values inside `config.obj_detect.yml` only.
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