Commit 5111debd authored by Adam Paquette's avatar Adam Paquette
Browse files

continued implementation of the config file in image_match

parent ccc8ca4a

bin/image_match.py

+16 −9
Original line number Diff line number Diff line
@@ -3,11 +3,15 @@ import os 


import argparse



sys.path.insert(0, os.path.abspath('../autocnet'))





from autocnet.utils.utils import find_in_dict

from autocnet.graph.network import CandidateGraph

from autocnet.fileio.io_controlnetwork import to_isis, write_filelist

from autocnet.fileio.io_yaml import read_yaml





def parse_arguments():

    parser = argparse.ArgumentParser()

    parser.add_argument('input_file', action='store', help='Provide the name of the file list/adjacency list')
@@ -19,7 +23,6 @@ def match_images(args, config_dict): 
    # Matches the images in the input file using various candidate graph methods

    # produces two files usable in isis



    '''

    try:

        cg = CandidateGraph.from_adjacency(find_in_dict(config_dict, 'inputfile_path') +

                                           args.input_file, basepath=find_in_dict(config_dict, 'basepath'))
@@ -35,10 +38,14 @@ def match_images(args, config_dict): 


    # Apply outlier detection

    cg.symmetry_checks()

    cg.ratio_checks()

    cg.ratio_checks(clean_keys=(find_in_dict(config_dict, 'ratio_checks')['clean_keys']),

                    ratio=find_in_dict(config_dict, 'ratio'),

                    mask=find_in_dict(config_dict, 'mask'),

                    mask_name=find_in_dict(config_dict, 'mask_name'),

                    single=find_in_dict(config_dict, 'single'))



    # Compute a homography and apply RANSAC

    cg.compute_fundamental_matrices(clean_keys=find_in_dict(config_dict, 'fundamental_matrics')['clean_keys'])

    cg.compute_fundamental_matrices(clean_keys=find_in_dict(config_dict, 'fundamental_matrices')['clean_keys'])



    cg.subpixel_register(clean_keys=find_in_dict(config_dict, 'subpixel_register')['clean_keys'],

                         template_size=find_in_dict(config_dict, 'template_size'),
@@ -49,7 +56,7 @@ def match_images(args, config_dict): 
                         tiled=find_in_dict(config_dict, 'tiled'))



    cg.suppress(clean_keys=find_in_dict(config_dict, 'suppress')['clean_keys'],

                k=find_in_dict(config_dict, 'keyword_arguments')['k'])

                k=find_in_dict(config_dict, 'suppress')['k'])



    cnet = cg.to_cnet(clean_keys=find_in_dict(config_dict, 'cnet_conversion')['clean_keys'],

                      isis_serials=True)
@@ -64,9 +71,9 @@ def match_images(args, config_dict): 
            targetname=find_in_dict(config_dict, 'targetname'),

            description=find_in_dict(config_dict, 'description'),

            username=find_in_dict(config_dict, 'username'))

    '''



if __name__ == '__main__':

    config = read_yaml()

    print(find_in_dict(config, 'fundamental_matrices'))

    # command_line_args = parse_arguments()

    # match_images(command_line_args, config)
 
    config = read_yaml('image_match_config.yml')

    single = find_in_dict(config, 'single')

    command_line_args = parse_arguments()

    match_images(command_line_args, config)

image_match_config.yml

+5 −4
Original line number Diff line number Diff line
@@ -17,8 +17,9 @@ match_features: 
ratio_checks:

    clean_keys:

        -

    keyword_arguments



    ratio: 0.8

    mask: None

    mask_name: None

    single: False
@@ -27,7 +28,7 @@ fundamental_matrices: 
    clean_keys:

        - ratio

        - symmetry

    keyword_arguments



    method:

    reproj_threshold:

    confidence:
@@ -43,14 +44,14 @@ subpixel_register: 
    max_x_shift: 1.0

    max_y_shift: 1.0

    tiled: False

    keyword_arguments



    upsampling:

    error_check: False



suppress:

    clean_keys:

        - fundamental

    keyword_arguments



    min_radius: 2

    k: 50

    error_k: 0.1