football4life's Introduction

Football Team Foul Detection

Intro to Deep Learning Project CS492, Fall 2021, KAIST.

Game Dataset

To install dataset, run Dataset/download_Soccernet.py and auto_trim.py

In each game folder, / Dataset/SoccerNet / trim_dir / league / year / match

'1_field_calib_ccbv.json',
'1_HQ.mkv', => First Half, Full Match
'1_player_boundingbox_maskrcnn.json', => RCNN Prediction from Giancos's data, 1st Half
'1_ResNET_TF2.npy',
'1_ResNET_TF2_PCA512.npy', => After PCA
'2_field_calib_ccbv.json',
'2_HQ.mkv',
'2_player_boundingbox_maskrcnn.json',
'2_ResNET_TF2.npy',
'2_ResNET_TF2_PCA512.npy',
'annotator.txt',
'Foul', => Trimmed Videos of Foul
'Labels-cameras.json', => Containing camera view(Close up player/main referee, Main Camera), time
'Labels-captioning.json', => Match Commentary, inaccurate
'Labels-v2.json', => Containing all events(kick-off, foul, card, etc) and which team commiting the events
'Labels.json', => Containing Events (Kickoff, Card, End of Match, Substitution) only
'labels_event.json', => Containing Foul, Yellow and Red card and Which team commits the foul
'Red card', => Trimmed Videos for Red Card
'video.ini', => Details about 1_HQ.mkv and 2_HQ.mkv
'video_with_duration.ini', => Details about 1_HQ.mkv and 2_HQ.mkv
'Yellow card' => Trimmed Videos of Yellow Card

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