Quickstart
Run tree detection on a single orthomosaic in a few steps.
Sample raster
A small test raster is included in the repository at assets/20240130_zf2tower_m3m_rgb_test_crop.tif. You can use it to try the commands below without needing your own data.
Using a preset configuration
CanopyRS ships with preset pipelines. The fastest way to get started is to use one of them directly via infer.py.
Single raster/orthomosaic input (-i):
python infer.py -c <CONFIG_NAME> -i <PATH_TO_TIF> -o <PATH_TO_OUTPUT_FOLDER>
Folder of already tiled geo-referenced images (-t):
python infer.py -c <CONFIG_NAME> -t <PATH_TO_TILES_FOLDER> -o <PATH_TO_OUTPUT_FOLDER>
Command-line arguments
| Argument | Description |
|---|---|
-c |
Config name (folder name under canopyrs/config/, see Presets for a list of predefined configs.) |
-i |
Input path to a single raster/orthomosaic |
-t |
Input path to a folder of geo-referenced .tif tiles |
-o |
Output path |
Understanding the output
The output folder will contain one subfolder per component that ran, containing output files such as:
- GeoPackage (
.gpkg) — for example predicted tree polygons with scores - COCO JSON — predictions in COCO format (used internally between components, can also be used to visualize per-tile predictions, see TODO)
If the chosen pipeline configuration produced a GeoDataFrame containing polygon results, it will be present at the root of your output folder.
Choosing the right preset
See Presets for full details.