Skip to main content

CLI Examples

Practical examples of common DroneDB CLI workflows.

Glob Patterns​

ddb accepts shell-style glob patterns wherever a path or list of paths is expected:

PatternMatches
*.JPGAll .JPG files in the current directory
images/*.tifAll .tif files directly under images/
**/*.lasAll .las files recursively
images/**/*All files under images/, recursively
images/The directory itself plus everything under it

Some shells (POSIX shells, PowerShell) expand globs before passing them to ddb. Quote the pattern (e.g., '**/*.JPG') if you want ddb to handle the expansion.

Sharing Datasets​

Share images to Hub or a self-hosted Registry:

# Share to Hub (default)
ddb share *.JPG

# Share to a specific server
ddb share *.JPG -s http://localhost:5000

# Share with a specific tag
ddb share *.JPG -t my-org/my-dataset

Tags follow the format: [server]/organization/dataset (server is optional).

Clone, Edit, and Push Workflow​

Clone an existing dataset, make modifications offline, then sync back:

# 1. Clone a dataset from Hub
ddb clone pierotofy/brighton-beach

# 2. Add new files
cd brighton-beach/
ddb add README.md new_photos/*.JPG

# 3. Push changes back
ddb push

# 4. (Optional) Change destination tag
ddb tag http://localhost:5000/my-org/brighton-copy
ddb push

Metadata Management​

Store custom JSON metadata on files or the entire dataset:

# Dataset-level metadata
ddb meta set pilot '{"name": "John Smith"}'
ddb meta get pilot --format json

# File-level metadata
ddb add photo.JPG
ddb meta add comments '{"text": "Nice one!", "author": "John S."}' -p photo.JPG
ddb meta get comments -p photo.JPG --format json

Plural keys (ending with s) are treated as lists; singular keys are single objects. Metadata is synced on push/pull.

Multispectral Workflow​

A typical flow for multispectral survey data processed with OpenDroneMap:

# 1. Index the original raw captures
ddb add images/

# 2. Merge per-band orthophotos from ODM output
ddb merge-multispectral \
  -o odm_orthophoto/multispectral.tif \
  odm_orthophoto/odm_orthophoto_blue.tif \
  odm_orthophoto/odm_orthophoto_green.tif \
  odm_orthophoto/odm_orthophoto_red.tif \
  odm_orthophoto/odm_orthophoto_nir.tif \
  odm_orthophoto/odm_orthophoto_rededge.tif

# 3. Mask border pixels
ddb mask odm_orthophoto/multispectral.tif

# 4. Add the merged result to the index
ddb add odm_orthophoto/multispectral_masked.tif

# 5. Share or push to Hub
ddb push

Terrain Analytics​

Generate contour lines​

# Contours every 10 m, simplified to 1 m
ddb contour dem.tif -o contours.geojson -i 10 -s 1

# 20 evenly spaced levels
ddb contour dem.tif -o contours.geojson -n 20

Mask orthophoto borders​

# Remove black borders
ddb mask orthophoto.tif

# Custom tolerance and output
ddb mask orthophoto.tif -o output.tif

# Search for white borders
ddb mask orthophoto.tif -w

Align rasters to a reference​

Correct georeferencing offsets by aligning to a more accurate reference:

# Similarity transform (default: translation + rotation + scale)
ddb align -i source.tif -r reference.tif -o aligned.tif

# Translation only (faster)
ddb align -i source.tif -r reference.tif -o aligned.tif -m translation

# Validate without applying
ddb align -i source.tif -r reference.tif --validate

See Also​