Metadata-Version: 2.1
Name: SoccerNet
Version: 0.0.40
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
        ```
        
        ## How to Download Games (Python)
        
        ```python
        from SoccerNet import SoccerNetDownloader
        
        mySoccerNetDownloader = SoccerNetDownloader(
            LocalDirectory="/path/to/soccernet/folder")
        
        # input password to download video (copyright protected)
        password = input("Password for videos? (contact the author):\n")
        mySoccerNetDownloader.password = password
        
        # Download SoccerNet v1
        mySoccerNetDownloader.downloadGames(files=["Labels.json"], split=["train","valid","test"]) # download labels
        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
        mySoccerNetDownloader.downloadGames(files=["1_ResNET_TF2.npy", "2_ResNET_TF2.npy"], split=["train","valid","test"]) # download Features
        
        
        # Download SoccerNet Test Set
        mySoccerNetDownloader.LocalDirectory = "/path/to/soccernet/challenge/folder"
        mySoccerNetDownloader.downloadGames(files=["1.mkv", "2.mkv"], split=["challenge"]) # download LQ Videos
        mySoccerNetDownloader.downloadGames(files=["1_HQ.mkv", "2_HQ.mkv", "video.ini"], split=["challenge"]) # download HQ Videos
        mySoccerNetDownloader.downloadGames(files=["1_ResNET_TF2.npy", "2_ResNET_TF2.npy"], split=["challenge"]) # download Features
        ```
        
        ## 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=["train", "valid", "test"])) # return list of games for training, validation and testing
        print(getListGames(split="v1")) # return list of games from SoccerNetv1 (train/valid/test)
        print(getListGames(split="challenge")) # return list of games for the challenge
        print(getListGames(split=["v1", "challenge"])) # return complete list of games
        
        ```
        
        ## [Coming soon...] How to extract features (TensorFlow 2)
        
        ```python
        from SoccerNet import FeatureExtractor
        
        myFeatureExtractor = FeatureExtractor(
            args.soccernet_dirpath, feature="ResNet", video="LQ", back_end="TF2")
        
        myFeatureExtractor.extractGameIndex(0)
        ```
        
        ## [Coming soon...] Tensorflow/Pytorch dataloader
        
        ```bash
        pip install scikit-video
        pip cudnn cudatoolkit=10.1
        pip install tensorflow
        pip install pytorch torchvision cudatoolkit=10.1
        pip install av
        
        # conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
        ```
        
        
        
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
