MPV python assignment templates

Using this repo

The recommended way of using the templates is as follows.

First, you clone the repository:

git clone 

Then, you create a new branch for your solutions:

cd mpv-python-assignment-templates
git checkout -b solutions

After that, you can work on your solutions, commiting as necessary.

In order to update the template, commit all your work and execute:

# download the new template version:
git checkout master
git pull
# and update your solutions branch:
git checkout solutions
git merge master

You can create conda environment with all required packages via the following for CPU:

conda create --name mpv-assignments-cpu-only python=3.10
conda activate mpv-assignments-cpu-only
pip3 install torch==1.12.1+cpu torchvision==0.13.1+cpu torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cpu
pip3 install kornia==0.6.10 tqdm notebook matplotlib opencv-contrib-python==4.7.0.68 seaborn tensorboard tensorboardX ipywidgets widgetsnbextension
pip3 install kornia_moons --no-deps

And following for GPU. You may need to change the cuda version to the actually installed one. For the GPU setup, if you have CUDA-capable GPU (if needed - change CUDA version in command). To find out your CUDA version, run nvidia-smi. You will see something like:

Mon Feb 20 16:49:46 2023       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.39       Driver Version: 460.39       CUDA Version: 11.2     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  GeForce GTX 108...  On   | 00000000:01:00.0 Off |                  N/A |
| 25%   44C    P8    18W / 250W |      1MiB / 11178MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
|   1  GeForce GTX 108...  On   | 00000000:06:00.0 Off |                  N/A |
|ERR!   54C    P0   ERR! / 250W |      1MiB / 11178MiB |     75%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+
                                                                               
+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+

In the example above, the CUDA version is 11.2, so you should use –extra-index-url https://download.pytorch.org/whl/cu112

conda create --name mpv-assignments-gpu python=3.10
conda activate mpv-assignments-gpu
pip3 install torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu112
pip3 install kornia==0.6.10 tqdm notebook matplotlib opencv-contrib-python==4.7.0.68 seaborn tensorboard tensorboardX ipywidgets widgetsnbextension
pip3 install kornia_moons --no-deps

For Apple Silicon devices (M1, M2 family) use:

conda create --name mpv-assignments-cpu-only python=3.10
conda activate mpv-assignments-cpu-only
conda install -c apple tensorflow-deps
pip3 install tensorflow-macos tensorflow-metal
pip3 install torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cpu
pip3 install kornia==0.6.10 tqdm notebook matplotlib opencv-contrib-python==4.7.0.68 seaborn tensorboard tensorboardX ipywidgets widgetsnbextension
pip3 install kornia_moons --no-deps

Keep in mind that the assignments and the assignment templates will be updated during the semester. Always pull the current template version before starting to work on an assignment!