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# Autonomous systems 1: Object detection

## The goal of the project

We want to take the [MobileNet](https://pytorch.org/hub/pytorch_vision_mobilenet_v2/) implementation with PyTorch and try to extend it.

The goal is to use some data from the [Food 101 dataset](https://www.kaggle.com/kmader/food41) and try to use it to extend MobileNet so that it can classify pictures of food as well.

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## How to set up an environment with Python
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Make sure you are using Python 3: `python --version`. On Ubuntu, you can probably use the `python3` command to resolve any ambiguities.

Create an environment directory, the packages you install with `pip` (for instance, PyTorch) will be stored there. I put it in the "env" directory.

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    virtualenv -p python3 env
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Activate the virtual environment:

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    # If you are using bash
    source env/bin/activate
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Your prompt should have if the activation of the virtual env worked.

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## Installing Jupyter

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If you want to use a Jupyter notebook, you can install Jupyter and all the required packages
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	pip install -r packages
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And then:

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    jupyter notebook
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Warning: You may have to run these commands *even if you have Jupyter installed on your machine already*, as it's set up to work with your packages when installed this way.

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## Installing PyTorch

You need to go on [the PyTorch page](https://pytorch.org/get-started/locally/#mac-anaconda) and choose from a selector the things you have, it will generate a command to paste in your terminal to install it.
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## Downloading the images

You need to download the images from [kaggle](https://www.kaggle.com/kmader/food41#1002850.jpg).