Load¶

Overview¶

Loading data is a two-step process. First, load your media, then load the annotations associated with them.

You will need to have a valid Tator token to load data into the database and a configuration yaml file for your project. Configuration YAML files are available per project in ai projects doc. See the CFE lab deployments for an example.

Currently, the aidata tool supports loading images and either VOC formatted xml files, or SDCAT formatted csv files which contain bounding box, saliency score and class and optionally cluster information, e.g.

image_path,class,score,area,saliency,x,y,xx,xy,w,h,cluster,image_width,image_height,crop_path
/mnt/UAV/Level-1/trinity-2_20240820T160209_Seymour/SONY_DSC-RX1RM2/trinity-2_20240820T160209_Seymour_DSC01706.JPG,Kelp,0.802138149738,537.0,205,0.8211770623742455,0.669683257918552,0.8257042253521126,0.6840120663650076,0.0045271629778671,0.0143288084464555,-1,7952,5304,/mnt/ML_SCRATCH/UAV/MBARI/uav-yolov5-30k/crops/3c59842f-ea08-5104-966f-609b76344619.jpg
/mnt/UAV/Level-1/trinity-2_20240820T160209_Seymour/SONY_DSC-RX1RM2/trinity-2_20240820T160209_Seymour_DSC01706.JPG,Kelp,0.7822825610640001,607.5,237,0.5596076458752515,0.6738310708898945,0.5674044265593562,0.6881598793363499,0.0077967806841047,0.0143288084464554,-1,7952,5304,/mnt/ML_SCRATCH/UAV/MBARI/uav-yolov5-30k/crops/e7e1cf68-a9c8-5c06-b872-1f0000b75891.jpg

What metadata is loaded from the media depends on the project configuration. The code that extracts the metadata is defined in a tap module that is designed per project per the following table. You should not need to set this - these should be captured in the project YAML configuration file "plugin" section as appropriate for the project but are listed here for reference. For example,

plugins:
  - name: "extractor"
    module: "mbari_aidata.plugins.extractors.tap_cfe_media"
    function: "extract_media"

Tap Name	Description
`tap_cfe_media`	Extracts metadata from CFE project image and video filenames. It identifies instrument types (ISIIS, SES, SINKER, MINION_FLUX, SNOW_CAM) and parses ISO timestamps and depth information.
`tap_i2map_media`	Extracts metadata from i2MAP image and video filenames. It parses dates, times, and depth from filenames and uses the `ephem` library to determine if the media was captured during day or night.
`tap_planktivore_media`	Extracts metadata from Planktivore image filenames. It supports parsing both ISO 8601 timestamps and high-resolution microsecond timestamps from camera filenames.
`tap_sdcat_csv`	Extracts data from SDCAT-generated CSV files. It prepares bounding box coordinates, labels, and image paths for loading.
`tap_sony_media`	Extracts detailed EXIF metadata from Sony images, including camera make and model, GPS coordinates (latitude, longitude, altitude), and the original capture timestamp.
`tap_vars_media`	Extracts metadata from VARS image filenames following the pattern `<mission>_<date>_<time>_<millis>.jpg`. It parses the mission name, capture time, and elapsed time.
`tap_voc`	Extracts object detection data from PASCAL VOC XML files. It parses image dimensions, bounding boxes, and labels, normalizing coordinates for database compatibility.

Step 1¶

Two types of media files can be loaded: images and videos; both need to be loaded before annotation data can be loaded. Media can be loaded individually, from a directory, or from a simple text file with an absolute path listing of each media, one file per line.

🖼️ Load images in a directory¶

aidata load images --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --input /Volumes/CFElab/2021-07-01/ --section 2021/07

🖼️ Load a single image¶

aidata load images --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --input /Volumes/CFElab/2021-07-01/video.mp4 --section 2021/07

🖼️ Load images from a text file¶

Suppose you have a text file images.txt with the following content:

/Volumes/CFElab/2021-07-01/image1.jpg
/Volumes/CFElab/2021-07-01/image20.jpg
/Volumes/CFElab/2021-07-01/image22.jpg

Load with:

aidata load images --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --input images.txt --section 2021/07

Note that the section is optional and by default all media will be loaded into the All Media section. The section will be created if it does not exist.

🖼️ Load and verify duplicates¶

For large image sets, skipping the duplicate check can be useful to speed up the loading process, but for small sets, this is recommended.

aidata load images --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --input images.txt --section 2021/07 --check-duplicates

🎥 Load videos¶

aidata load videos --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --input /Volumes/CFElab/2021-07-01/ --section 2021/07

Tip

Use the --dry-run option to see what will be loaded without actually loading the data.

aidata load images --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --input /Volumes/CFElab/2021-07-01/ --dry-run --section 2021/07

Step 2¶

🏷️ Load boxes from a directory¶

aidata load boxes --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --input /Volumes/CFElab/2021-07-01/ --version Baseline

Use the --help option for more information on the available options for aidata load boxes.

Advanced¶

Load cluster data from a SDCAT formatted CSV file¶

To update the cluster data of a previously loaded ROI, you can use the following command with a CSV file containing cluster information:

image_path,class,score,area,saliency,x,y,xx,xy,w,h,cluster,image_width,image_height,crop_path
/mnt/UAV/Level-1/trinity-2_20240820T160209_Seymour/SONY_DSC-RX1RM2/trinity-2_20240820T160209_Seymour_DSC01706.JPG,Kelp,0.802138149738,537.0,205,0.8211770623742455,0.669683257918552,0.8257042253521126,0.6840120663650076,0.0045271629778671,0.0143288084464555,5,7952,5304,/mnt/ML_SCRATCH/UAV/MBARI/uav-yolov5-30k/crops/45333.jpg
/mnt/UAV/Level-1/trinity-2_20240820T160209_Seymour/SONY_DSC-RX1RM2/trinity-2_20240820T160209_Seymour_DSC01706.JPG,Kelp,0.7822825610640001,607.5,237,0.5596076458752515,0.6738310708898945,0.5674044265593562,0.6881598793363499,0.0077967806841047,0.0143288084464554,6,7952,5304,/mnt/ML_SCRATCH/UAV/MBARI/uav-yolov5-30k/crops/45334.jpg

aidata load clusters --token $TATOR_TOKEN --config https://docs.mbari.org/internal/ai/projects/config/config_uav.yml --input clusters.csv --version Baseline

This will update the clusters to 5 and 6 respectively for the corresponding localizations in the database.

Load from a REDIS queue¶

Loading of video and video annotations is also supported through a REDIS server. To load video and video annotations from a REDIS queue, you can use the following command:

aidata load queue --config https://docs.mbari.org/internal/ai/projects/config/config_i2map.yml --token $TATOR_TOKEN

To reset the queue, removing any previously cached data, use the --reset option:

aidata load queue --config https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml --token $TATOR_TOKEN --reset

Overriding config YAML¶

You can download and modify the configuration file for your project if needed. For example, to specify a local mount point:

Download the configuration YAML for your project from the ai projects doc and modify the mounts section to specify the local path and host for your media. For example:

curl -o config.yml https://docs.mbari.org/internal/ai/projects/config/config_cfe.yml

Then modify the mounts section in config.yml to point to your local media path and host:

mounts:
  - name: "image"
    path: "/Volumes/CFElab"
    host: "https://mantis.shore.mbari.org"

Then use the --config option to specify the modified configuration file:

aidata load images --token $TATOR_TOKEN --config config.yml --input /Volumes/CFElab/2021-07-01/ --section 2021/07

last updated: 2026-02-08