d7896c80ae2fdfb5f96aec3fe75d14141ade4a5a,deeplabcut/utils/conversioncode.py,,analyze_videos_converth5_to_csv,#Any#Any#,148

Before Change

    deeplabcut.analyze_videos_converth5_to_csv("/media/alex/experimentaldata/cheetahvideos",".mp4")

    
    start_path = os.getcwd()
    os.chdir(videopath)
    Videos = [
        fn
        for fn in os.listdir(os.curdir)
        if (videotype in fn) and ("_labeled.mp4" not in fn)
    ]  // exclude labeled-videos!

    Allh5files = [
        fn for fn in os.listdir(os.curdir) if (".h5" in fn) and ("resnet" in fn)
    ]

    for video in Videos:
        vname = Path(video).stem
        // Is there a scorer for this?
        PutativeOutputFiles = [fn for fn in Allh5files if vname in fn]
        for pfn in PutativeOutputFiles:
            scorer = pfn.split(vname)[1].split(".h5")[0]
            if "DLC" in scorer or "DeepCut" in scorer:
                DC = pd.read_hdf(pfn, "df_with_missing")
                print("Found output file for scorer:", scorer)
                print("Converting to csv...")
                DC.to_csv(pfn.split(".h5")[0] + ".csv")

    os.chdir(str(start_path))
    print("All pose files were converted.")


def merge_windowsannotationdataONlinuxsystem(cfg):

After Change

            continue
        vname = Path(video).stem
        for file in h5_files:
            if vname in file:
                scorer = file.split(vname)[1].split(".h5")[0]
                if "DLC" in scorer or "DeepCut" in scorer:
                    print("Found output file for scorer:", scorer)
                    print(f"Converting {file}...")
                    df = pd.read_hdf(file, "df_with_missing")
                    df.to_csv(file.replace(".h5", ".csv"))
    print("All pose files were converted.")


def merge_windowsannotationdataONlinuxsystem(cfg):

Instances