- Python 3
For the installation I recommend a python venv.
git clone git@github.com:vislearn/3dcv-students.git
cd 3dcv/
python3 -m venv .
source bin/activate
pip install -r requirements.txtDownload Python here. Make sure that the installer adds Python to your PATH.
In PowerShell run
git clone git@github.com:vislearn/3dcv-students.git(if you don't use git, just download and extract the zip file)
cd .\3dcv\
pip install torch torchvision -f https://download.pytorch.org/whl/torch_stable.html
pip install -r .\requirements.txtIn order to edit the notebooks run
jupyter-labto start the local webserver.
If the notebook home page does not show up immediately, open http://localhost:8888 in your browser.
Now, just open one of the task notebooks and start editing.
├── 1.0-tl-scientific-python.ipynb <- The Notebooks, containing your tasks
│
├── ...
│
├── LICENSE <- The License
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├── README.md <- The top-level README with installation instructions
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├── data <- The necessary data files, e.g. datasets
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├── models <- Trained and serialized models, model predictions, or model summaries
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├── requirements.txt <- The requirements file to setup the environment
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├── task.pdf <- Detailed information about your tasks
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├── vll <- Boilerplate source code provided by us
│ │
│ ├── data <- Scripts to download or generate data
│ │
│ ├── model <- Scripts defining the neural network models
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│ ├── utils <- Scripts utilities used during data generation or training
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│ ├── validate <- Scripts to validate models
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│ └── visualize <- Scripts to create exploratory and results oriented visualizations