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Usage

Configurations

The currently avaliable configs are the following:

Learneable Pooling:

configs/learnablepooling/soccernet_netvlad++_resnetpca512.py

configs/learnablepooling/json_avgpool_resnetpca512.py
configs/learnablepooling/json_maxpool_resnetpca512.py
configs/learnablepooling/json_netrvlad_resnetpca512.py
configs/learnablepooling/json_netvlad_resnetpca512.py
configs/learnablepooling/json_avgpool++_resnetpca512.py
configs/learnablepooling/json_maxpool++_resnetpca512.py
configs/learnablepooling/json_netrvlad++_resnetpca512.py
configs/learnablepooling/json_netvlad++_resnetpca512.py

CALF:

configs/contextawarelossfunction/json_soccernet_calf_resnetpca512.py

configs/contextawarelossfunction/soccernet_resnetpca512.py

PTS:

configs/e2espot/e2espot.py
configs/e2espot/e2espot_ocv.py

Training

python tools/train.py {config}

Train example

python tools/train.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py

Train example with custom config file

python tools/train.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py \
    --cfg-options training.max_epochs=10 \
        dataset.train.data_root=/datasets/SoccerNet \
        dataset.valid.data_root=/datasets/SoccerNet \
        dataset.train.path=/datasets/SoccerNet/ResNET_PCA512/train/annotations.json \
        dataset.valid.path=/datasets/SoccerNet/ResNET_PCA512/valid/annotations.json

Inference

python tools/infer.py {config}

Inference example

python tools/infer.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py

For E2E, provide the model weights path

python tools/infer.py \
    configs/e2espot/e2espot.py --weights /path/to/your/model/weights

Note:- If you don't provide the path to the model weights, the weights are assumed to be inside the cfg.work_dir as "best_checkpoint.pt"

Inference example with custom config file

python tools/infer.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py \
    --cfg-options dataset.test.data_root=/datasets/SoccerNet \
        dataset.test.path=/datasets/SoccerNet/ResNET_PCA512/test/annotations.json

Evaluation

python tools/evaluate.py {config}

Evaluation example

python tools/evaluate.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py

Evaluation example with custom config file

python tools/evaluate.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py \
    --cfg-options dataset.test.path=/datasets/SoccerNet/ResNET_PCA512/test/annotations.json \
    dataset.test.metric=tight

If you don't see any results, you might need to specify the path to your results file

python tools/evaluate.py \
    configs/e2espot/e2espot.py \
    --cfg-options dataset.test.results=/outputs/e2e/rny008_gsm_150/results_spotting_test.recall.json.gz

Try to provide full path to the results, if you do not see any results.

So for a custom evaluation on test set, it might look something like this

python tools/evaluate.py \
    configs/e2espot/e2espot.py \
    --cfg-options dataset.test.path=/datasets/224p/test/annotations.json \
    dataset.test.data_root=/datasets/224p/test \
    dataset.test.results=outputs/e2e/rny008_gsm_150/results_spotting_test.recall.json.gz \
    dataset.test.metric=tight

Visualization

python tools/visualize.py {config}

Visualization example

python tools/visualize.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py

Visualization example with custom config file

python tools/visualize.py \
    configs/learnablepooling/json_netvlad++_resnetpca512.py \
    --cfg-options dataset.test.results=/outputs/learnablepooling/json_netvlad++_resnetpca512/results_spotting_test/england_epl/2014-2015/2015-05-17_-_18-00_Manchester_United_1_-_1_Arsenal/1_ResNET_TF2_PCA512/results_spotting.json \
    dataset.test.path=/home/ybenzakour/datasets/SoccerNet/england_epl/2014-2015/2015-05-17_-_18-00_Manchester_United_1_-_1_Arsenal/1_224p.mkv \
    visualizer.threshold=0.2