aligning.RmdTo align multimedia files, it is necessary at least the photo identification data and one more data source, such as video files. See Extracting metadata of multimedia files.
# read photo id data
photoid <- utils::read.csv(file = "/Volumes/mydisk/MAMMals/photoid.csv")
# check photos with no individual identification
ignore.photos <- photoid[is.na(photoid$camera.PHOTOID), 'camera.photo_filename']
# extract metadata, ignore photos with no ID, export .csv file and assign photoid to data_photoid
photos_metadata <- MAMMals::getPhotoMetadata(
ROOTfolderpath = photo_folderpath,
extension = '.jpg',
ignore = ignore.photos,
timezone = "America/Sao_Paulo",
export = NULL,
data_photoid = photoid[, c("camera.photo_filename","camera.PHOTOID")]
)
# extract metadata of drone video files
videos_metadata <- MAMMals::getVideoMetadata(
ROOTfolderpath = video_folderpath,
extension = '.mp4',
include_srt_datetime = FALSE,
ignore = NULL,
timezone = "America/Sao_Paulo",
export = NULL
)It is also possible to align multiple data sources. For example, extract the metadata of audio files with the getAudioMetadata(). If .wav or .mp3 audio files are available, simply pass the full path where all the audio files are located. As common used recorders use timestamped filenames, it is possible to retrieve the date and time from the filename.
audios_metadata = MAMMals::getAudioMetadata(
ROOTfolderpath,
extension = '.wav',
ignore = NULL,
filter_folder = NULL,
is_timestamp_filename = FALSE,
format_timestamp_filename = "ymd_hms",
timezone = 'America/Sao_Paulo',
export = paste0(export_data_folder, '/', 'test_audio_metadata.csv') )With photo-identification and video metadata available, it is possible to align both data sources to subset only media files containing photo-identification data. The function selectVideos uses the timestamp from the camera images and the drone videos to look for photo identification data taken during the video sampling. The select function then calculates the time of each photograph in the video (or audio with the selectAudios()).
selected_videos <- MAMMals::selectVideos(
data = photos_metadata,
data_datetime = NULL,
video_metadata = videos_metadata,
video_datetime = "video",
format_data_datetime = "%Y/%m/%d %H:%M:%S",
keep_all = FALSE,
export = NULL,
timezone = "America/Sao_Paulo")
#> During 2 video(s), 11 photo(s) were taken of 2 individual(s)
head(selected_videos)
#> camera.photo_path camera.photo_filename camera.PHOTOID
#> 1 /Volumes/mydisk/MAMMals/photoid 6Q1A0177.JPG L_24
#> 2 /Volumes/mydisk/MAMMals/photoid 6Q1A0178.JPG L_24
#> 3 /Volumes/mydisk/MAMMals/photoid 6Q1A0179.JPG L_24
#> 4 /Volumes/mydisk/MAMMals/photoid 6Q1A0180.JPG L_26
#> 5 /Volumes/mydisk/MAMMals/photoid 6Q1A0181.JPG L_26
#> 6 /Volumes/mydisk/MAMMals/photoid 6Q1A0182.JPG L_26
#> camera.photo_filename_exif camera.datetime_GPS_UTC camera.datetime_local
#> 1 6Q1A0177.JPG 2019-05-22 15:05:14 2019-05-22 12:05:15
#> 2 6Q1A0178.JPG 2019-05-22 15:05:14 2019-05-22 12:05:15
#> 3 6Q1A0179.JPG 2019-05-22 15:05:29 2019-05-22 12:05:30
#> 4 6Q1A0180.JPG 2019-05-22 15:05:59 2019-05-22 12:06:01
#> 5 6Q1A0181.JPG 2019-05-22 15:06:14 2019-05-22 12:06:29
#> 6 6Q1A0182.JPG 2019-05-22 15:06:14 2019-05-22 12:06:29
#> camera.CreateDate camera.TimeZone camera.TimeZoneCity
#> 1 2019-05-22 12:05:15 -03:00 Sao Paulo
#> 2 2019-05-22 12:05:15 -03:00 Sao Paulo
#> 3 2019-05-22 12:05:30 -03:00 Sao Paulo
#> 4 2019-05-22 12:06:01 -03:00 Sao Paulo
#> 5 2019-05-22 12:06:29 -03:00 Sao Paulo
#> 6 2019-05-22 12:06:29 -03:00 Sao Paulo
#> camera.DaylightSavings camera.CanonModelID camera.GPSLatitudeRef
#> 1 Off EOS 7D Mark II South
#> 2 Off EOS 7D Mark II South
#> 3 Off EOS 7D Mark II South
#> 4 Off EOS 7D Mark II South
#> 5 Off EOS 7D Mark II South
#> 6 Off EOS 7D Mark II South
#> camera.GPSLongitudeRef camera.GPSMapDatum camera.GPSAltitude
#> 1 West WGS-84 3.9 m Above Sea Level
#> 2 West WGS-84 3.9 m Above Sea Level
#> 3 West WGS-84 3.5 m Above Sea Level
#> 4 West WGS-84 1.1 m Below Sea Level
#> 5 West WGS-84 3.6 m Below Sea Level
#> 6 West WGS-84 3.6 m Below Sea Level
#> camera.direction.angle camera.direction.angle.ref camera.GPSLatitude
#> 1 226 Magnetic North 28 deg 29' 44.91" S
#> 2 226 Magnetic North 28 deg 29' 44.91" S
#> 3 167 Magnetic North 28 deg 29' 44.87" S
#> 4 241 Magnetic North 28 deg 29' 44.77" S
#> 5 247 Magnetic North 28 deg 29' 44.77" S
#> 6 246 Magnetic North 28 deg 29' 44.77" S
#> camera.GPSLongitude camera.latitude camera.longitude
#> 1 48 deg 45' 35.74" W -28.49581 -48.75993
#> 2 48 deg 45' 35.74" W -28.49581 -48.75993
#> 3 48 deg 45' 35.69" W -28.49580 -48.75991
#> 4 48 deg 45' 35.74" W -28.49577 -48.75993
#> 5 48 deg 45' 35.72" W -28.49577 -48.75992
#> 6 48 deg 45' 35.72" W -28.49577 -48.75992
#> video.path video.local_start_datetime
#> 1 /Volumes/mydisk/MAMMals/videos/DJI_0042.MP4 2019-05-22 11:59:05
#> 2 /Volumes/mydisk/MAMMals/videos/DJI_0042.MP4 2019-05-22 11:59:05
#> 3 /Volumes/mydisk/MAMMals/videos/DJI_0042.MP4 2019-05-22 11:59:05
#> 4 /Volumes/mydisk/MAMMals/videos/DJI_0042.MP4 2019-05-22 11:59:05
#> 5 /Volumes/mydisk/MAMMals/videos/DJI_0042.MP4 2019-05-22 11:59:05
#> 6 /Volumes/mydisk/MAMMals/videos/DJI_0042.MP4 2019-05-22 11:59:05
#> video.local_end_datetime video.duration video.photoid_time video.file
#> 1 2019-05-22 12:14:48 00:15:43.72 00:06:10 DJI_0042.MP4
#> 2 2019-05-22 12:14:48 00:15:43.72 00:06:10 DJI_0042.MP4
#> 3 2019-05-22 12:14:48 00:15:43.72 00:06:25 DJI_0042.MP4
#> 4 2019-05-22 12:14:48 00:15:43.72 00:06:56 DJI_0042.MP4
#> 5 2019-05-22 12:14:48 00:15:43.72 00:07:24 DJI_0042.MP4
#> 6 2019-05-22 12:14:48 00:15:43.72 00:07:24 DJI_0042.MP4