Official implementation of Spiideo's contribution to the 2023 SoccerNet Camera Calibration challange.
It includes a modified version of the SoccerNet Camera Calibration Development Kit in sncalib.
Install pytorch3d following it's installation instaructions, for example
python -mpip install --no-cache-dir pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py38_cu113_pyt1120/download.html
Install remaining requirements and setup python to run the modules from the checked out source
python -mpip install -r requirements.txt
python setup.py develop --user
Download the SoccerNet into data/SoccerNet/calibration-2023
from SoccerNet.Downloader import SoccerNetDownloader as SNdl
soccerNetDownloader = SNdl(LocalDirectory="data/SoccerNet/calibration-2023")
soccerNetDownloader.downloadDataTask(task="calibration-2023", split=["train", "valid", "test", "challenge"])Run the dataloader to display the images and generated segmentations:
python soccersegcal/dataloader.py
Train the segmentation model (add --help to se availible options):
python soccersegcal/train.py
To monitor training progress, compare different runs and get hold of the resulting checkpoint.ckpt:
mlflow ui
The checkpoint can also be found by digging through the mlruns dir.
To use the trained segmentation model to estimate camera parameters for the first two samples (index 0 and 1) in the validation set while visualizing the optimization:
python soccersegcal/estimate_cameras.py -c path/to/segmentation/checkpoint.ckpt -i [0,1] -s
To estimate all the cameras in the test set without visualisation (faster):
python soccersegcal/estimate_cameras.py -c path/to/segmentation/checkpoint.ckpt -p test
To se other options:
python soccersegcal/estimate_cameras.py --help
The estimated cameras will be saved in the cams_out directory. To run the SoccerNet evaluation on them:
python sncalib/evaluate_camera.py -s data/SoccerNet/calibration-2023/ --split test -p cams_out/
Pretrained weights can be downloaded from the table below. It also lists hyperparameters with non-default values.
| Hyperparameters | Combined Metric | Accuracy@5 | Completeness | |
|---|---|---|---|---|
| epochs=27 | 0.53 | 52.95 | 99.96 | snapshot.ckpt |