How to launch CARS

cars command line is the entry point for CARS to run the 3D pipeline.

cars -h

usage: cars [-h] [--loglevel {DEBUG,INFO,PROGRESS,WARNING,ERROR,CRITICAL}] [--version] conf

CARS: CNES Algorithms to Reconstruct Surface

positional arguments:
  conf                  Inputs Configuration File

optional arguments:
  -h, --help            show this help message and exit
  --loglevel {DEBUG,INFO,PROGRESS,WARNING,ERROR,CRITICAL}
                        Logger level (default: PROGRESS. Should be one of (DEBUG, INFO, PROGRESS, WARNING, ERROR, CRITICAL)
  --version, -v         show program's version number and exit

CARS cli takes only one .json or .yaml (or .yml) file as command line argument:

cars configfile.json
cars configfile.yaml
cars configfile.yml

Warning

A least 2 Go of RAM must be available. CARS will use 50% of total RAM.

Note that cars-starter script can be used to instantiate this configuration file.

cars-starter  -h

usage: cars-starter [-h] -il [input.{tif,XML} ...] -out out_dir [--full] [--check]

Helper to create configuration file
options:
  -h, --help            show this help message and exit
  -il [input.{tif,XML} ...]
                          Input sensor list
  -out out_dir          Output directory
  --full                Fill all default values
  --check               Check inputs

Finally, an output used_conf.json file will be created on the output directory. This file contains all the parameters used during execution and can be used as an input configuration file to re-run cars.

Here is a reminder of what a basic file configuration should look like :

YAML JSON Copy

---
input:
  sensors:
    one: img1.tif
    two: img2.tif
orchestrator:
  mode: multiprocessing
  nb_workers: 110
  max_ram_per_worker: 6000
output:
  directory: outresults

{
    "input": {
        "sensors": {
            "one": "img1.tif",
            "two": "img2.tif"
        }
    },
    "orchestrator": {
        "mode": "multiprocessing",
        "nb_workers": 110,
        "max_ram_per_worker": 6000
    },
    "output": {
        "directory": "outresults"
    }
}