NLeSC / PattyAnalytics

scripts/registration.py

#!/usr/bin/env python2.7
"""Registration script.

Usage:
  registration.py [-h] [-d <sample>] [-U] [-u <upfile>] [-c <camfile>] <source> <drivemap> <footprint> <output>

Positional arguments:
  source       Source LAS file
  drivemap     Target LAS file to map source to
  footprint    Footprint for the source LAS file
  output       file to write output LAS to

Options:
  -d <sample>  Downsample source pointcloud to a percentage of number of points
               [default: 0.1].
  -v <voxel>   Downsample source pointcloud using voxel filter to speedup ICP
               [default: 0.05]
  -s <scale>   User override for initial scale factor
  -U           Dont trust the upvector completely and estimate it in
               this script, too
  -u <upfile>  Json file containing the up vector relative to the pointcloud.
  -c <camfile> CSV file containing all the camera postionions. [UNIMPLEMENTED]
"""

from __future__ import print_function
from docopt import docopt

import numpy as np
import os
import json
from patty.utils import (load, save, log)
from patty.srs import (set_srs, force_srs)

from patty.registration import (
    coarse_registration,
    fine_registration,
    initial_registration,
    )

if __name__ == '__main__':

    ####
    # Parse comamnd line arguments

    args = docopt(__doc__)

    sourcefile = args['<source>']
    drivemapfile = args['<drivemap>']
    footprintcsv = args['<footprint>']

The name footprintcsv does not conform to the constant naming conventions ((([A-Z_][A-Z0-9_]*)|(__.*__))$).

    foutLas = args['<output>']
    up_file = args['-u']

    if args['-U']:
        Trust_up = False
    else:
        Trust_up = True

    try:
        Downsample = float(args['-d'])
    except KeyError:
        Downsample = 0.1

    try:
        Voxel = float(args['-v'])
    except KeyError:
        Voxel = 0.05

    try:
        Initial_scale = float(args['-s'])
    except:
        Initial_scale = None

    assert os.path.exists(sourcefile), sourcefile + ' does not exist'
    assert os.path.exists(drivemapfile), drivemapfile + ' does not exist'
    assert os.path.exists(footprintcsv), footprintcsv + ' does not exist'

    #####
    # Setup * the low-res drivemap
    #       * footprint
    #       * pointcloud
    #       * up-vector

    log("Reading drivemap", drivemapfile)
    drivemap = load(drivemapfile)
    force_srs(drivemap, srs="EPSG:32633")

    log("Reading footprint", footprintcsv)
    footprint = load(footprintcsv)
    force_srs(footprint, srs="EPSG:32633")
    set_srs(footprint, same_as=drivemap)

    log("Reading object", sourcefile)
    pointcloud = load(sourcefile)

    Up = None
    try:
        with open(up_file) as f:
            dic = json.load(f)
        Up = np.array(dic['estimatedUpDirection'])
        log("Reading up_file", up_file)
    except:
        log("Cannot parse upfile, skipping")

    initial_registration(pointcloud, Up, drivemap,
                         trust_up=Trust_up, initial_scale=Initial_scale)
    save(pointcloud, "initial.las")
    center = coarse_registration(pointcloud, drivemap, footprint, Downsample)
    save(pointcloud, "coarse.las")
    fine_registration(pointcloud, drivemap, center, voxelsize=Voxel)

    save(pointcloud, foutLas)