Metadata-Version: 2.1
Name: SoccerNet
Version: 0.0.91
Summary: SoccerNet SDK
Home-page: https://github.com/SilvioGiancola/SoccerNetv2
Author: Silvio Giancola
Author-email: silvio.giancola@kaust.edu.sa
License: MIT
Description: # SOCCERNETV2
        
        ```bash
        conda create -n SoccerNet python pip
        pip install SoccerNet
        ```
        
        ## Structure of the data data for each game
        
        - SoccerNet main folder
          - Leagues (england_epl/europe_uefa-champions-league/france_ligue-1/...)
            - Seasons (2014-2015/2015-2016/2016-2017)
              - Games (format: "{Date} - {Time} - {HomeTeam} {Score} {AwayTeam}")
                - SoccerNet-v2
                  - 1_HQ.mkv (HQ video 1st half)
                  - 2_HQ.mkv (HQ video 2nd half)
                  - video.ini (information on start/duration for each half of the game in the HQ video, in second)
                  - 1.mkv (LQ video 1st half - timmed with start/duration from HQ video - resolution 224*398 - 25 fps)
                  - 2.mkv (LQ video 2nd half - timmed with start/duration from HQ video - resolution 224*398 - 25 fps)
                  - Labels-v2.json (Labels from SoccerNet-v2 - action spotting)
                  - Labels-camera.json (Labels from SoccerNet-v1 - camera shot segmentation)
                  - 1_ResNET_TF2.npy (ResNET features @2fps for 1st half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit))
                  - 2_ResNET_TF2.npy (ResNET features @2fps for 2nd half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit))
                  - 1_ResNET_TF2_PCA512.npy (ResNET features @2fps for 1st half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit), with dimensionality reduced to 512 using PCA)
                  - 2_ResNET_TF2_PCA512.npy (ResNET features @2fps for 2nd half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit), with dimensionality reduced to 512 using PCA)
                  - 1_ResNET_5fps_TF2.npy (ResNET features @5fps for 1st half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit))
                  - 2_ResNET_5fps_TF2.npy (ResNET features @5fps for 2nd half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit))
                  - 1_ResNET_5fps_TF2_PCA512.npy (ResNET features @5fps for 1st half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit), with dimensionality reduced to 512 using PCA)
                  - 2_ResNET_5fps_TF2_PCA512.npy (ResNET features @5fps for 2nd half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit), with dimensionality reduced to 512 using PCA)
                  - 1_ResNET_25fps_TF2.npy (ResNET features @25fps for 1st half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit))
                  - 2_ResNET_25fps_TF2.npy (ResNET features @25fps for 2nd half from SoccerNet-v2, [extracted using TF2](https://github.com/SilvioGiancola/SoccerNetv2-DevKit))
        
                - Legacy from SoccerNet-v1
                  - Labels.json (Labels from SoccerNet-v1 - action spotting for goals/cards/subs only)
                  - 1_C3D.npy (C3D features @2fps for 1st half from SoccerNet-v1)
                  - 2_C3D.npy (C3D features @2fps for 2nd half from SoccerNet-v1)
                  - 1_C3D_PCA512.npy (C3D features @2fps for 1st half from SoccerNet-v1, with dimensionality reduced to 512 using PCA)
                  - 2_C3D_PCA512.npy (C3D features @2fps for 2nd half from SoccerNet-v1, with dimensionality reduced to 512 using PCA)
                  - 1_I3D.npy (I3D features @2fps for 1st half from SoccerNet-v1)
                  - 2_I3D.npy (I3D features @2fps for 2nd half from SoccerNet-v1)
                  - 1_I3D_PCA512.npy (I3D features @2fps for 1st half from SoccerNet-v1, with dimensionality reduced to 512 using PCA)
                  - 2_I3D_PCA512.npy (I3D features @2fps for 2nd half from SoccerNet-v1, with dimensionality reduced to 512 using PCA)
                  - 1_ResNET.npy (ResNET features @2fps for 1st half from SoccerNet-v1)
                  - 2_ResNET.npy (ResNET features @2fps for 2nd half from SoccerNet-v1)
                  - 1_ResNET_PCA512.npy (ResNET features @2fps for 1st half from SoccerNet-v1, with dimensionality reduced to 512 using PCA)
                  - 2_ResNET_PCA512.npy (ResNET features @2fps for 2nd half from SoccerNet-v1, with dimensionality reduced to 512 using PCA)
        
        
        ## How to Download Games (Python)
        
        ```python
        from SoccerNet import SoccerNetDownloader
        
        mySoccerNetDownloader = SoccerNetDownloader(LocalDirectory="/path/to/soccernet")
        
        # Download SoccerNet labels and features
        mySoccerNetDownloader.downloadGames(files=["Labels.json"], split=["train","valid","test"]) # download labels
        mySoccerNetDownloader.downloadGames(files=["Labels-v2.json"], split=["train","valid","test"]) # download labels SN v2
        mySoccerNetDownloader.downloadGames(files=["Labels-cameras.json"], split=["train","valid","test"]) # download labels for camera shot
        mySoccerNetDownloader.downloadGames(files=["1_ResNET_TF2.npy", "2_ResNET_TF2.npy"], split=["train","valid","test"]) # download Features
        mySoccerNetDownloader.downloadGames(files=["1_ResNET_TF2_PCA512.npy", "2_ResNET_TF2_PCA512.npy"], split=["train","valid","test"]) # download Features reduced with PCA
        
        # Download SoccerNet videos (require password from NDA to download videos)
        mySoccerNetDownloader.password = input("Password for videos? (contact the author):\n")
        mySoccerNetDownloader.downloadGames(files=["1.mkv", "2.mkv"], split=["train","valid","test"]) # download LQ Videos
        mySoccerNetDownloader.downloadGames(files=["1_HQ.mkv", "2_HQ.mkv", "video.ini"], split=["train","valid","test"]) # download HQ Videos
        
        # Download SoccerNet Challenge set (require password from NDA to download videos)
        mySoccerNetDownloader.downloadGames(files=["1_ResNET_TF2.npy", "2_ResNET_TF2.npy"], split=["challenge"]) # download Features
        mySoccerNetDownloader.downloadGames(files=["1_ResNET_TF2_PCA512.npy", "2_ResNET_TF2_PCA512.npy"], split=["challenge"]) # download Features reduced with PCA
        mySoccerNetDownloader.downloadGames(files=["1.mkv", "2.mkv", "video.ini"], split=["challenge"]) # download LQ Videos (require password from NDA)
        mySoccerNetDownloader.downloadGames(files=["1_HQ.mkv", "2_HQ.mkv", "video.ini"], split=["challenge"]) # download HQ Videos (require password from NDA)
        
        ```
        
        ## How to read the list Games (Python)
        
        ```python
        from SoccerNet import getListGames
        print(getListGames(split="train")) # return list of games recommended for training
        print(getListGames(split="valid")) # return list of games recommended for validation
        print(getListGames(split="test")) # return list of games recommended for testing
        print(getListGames(split="challenge")) # return list of games recommended for challenge
        print(getListGames(split=["train", "valid", "test", "challenge"])) # return list of games for training, validation and testing
        print(getListGames(split="v1")) # return list of games from SoccerNetv1 (train/valid/test)
        ```
        
        
        
Keywords: SoccerNet,SDK,Spotting,Football,Soccer,Video
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Description-Content-Type: text/markdown
