MacOS 13 Apple Silicon (M1 or M2 chip) with GPU acceleration

1. This was tested on macOS Ventura (13.2.1)

2. Install Miniforge for Apple Silicon. (See project page for more info.)

3. Create a new environment for pixplot:

conda create --name pixplot python=3.9

conda activate pixplot

4. Install the required packages for Apple's support of Tensorflow on the M1 chip:

conda install -c apple tensorflow-deps
python -m pip install tensorflow-macos
python -m pip install tensorflow-metal

5. Clone pixplot:

git clone https://github.com/YaleDHLab/pix-plot.git

6. Adjust the install_requires section of setup.py to read as follows:

 install_requires=[
    'cmake',
    'Cython',
    'glob2',
    'h5py',
    'iiif-downloader',
    'matplotlib',
    'numpy==1.23.5',
    'numba',
    'pytz',
    'pointgrid>=0.0.2',
    'python-dateutil>=2.8.0',
    'scikit-learn',
    'scipy',
    'six',
    'tqdm',
    'umap-learn',
    'yale-dhlab-rasterfairy>=1.0.3',
    'yale-dhlab-keras-preprocessing>=1.1.1',
  ],

6. Install:

python setup.py install

7. Temporary fixes till we figure things out:

pip install --force matplotlib
pip install --force scipy
pip install --force numba

8. Run:

time pixplot --images="datasets/oslomini/images/*.jpg" --metadata="datasets/oslomini/metadata/metadata.csv" --shuffle