Loading bin/image_match.py +9 −5 Original line number Diff line number Diff line import sys import os import argparse from autocnet.utils.utils import find_in_dict Loading @@ -13,10 +16,10 @@ def parse_arguments(): return args def match_images(args, config_dict): # print(find_in_dict(config_dict, 'to_isis')) # 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')) Loading Loading @@ -46,7 +49,7 @@ 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, 'suppress')['keyword_arguments']['k']) k=find_in_dict(config_dict, 'keyword_arguments')['k']) cnet = cg.to_cnet(clean_keys=find_in_dict(config_dict, 'cnet_conversion')['clean_keys'], isis_serials=True) Loading @@ -61,8 +64,9 @@ 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() command_line_args = parse_arguments() match_images(command_line_args, config) print(find_in_dict(config, 'fundamental_matrices')) # command_line_args = parse_arguments() # match_images(command_line_args, config) image_match_config.yml +19 −10 Original line number Diff line number Diff line Loading @@ -13,18 +13,24 @@ match_features: # Any clean keys being passed in requires a method to have been used on the candidate graph object # before the key can be passed in ratio_checks: clean_keys: - keyword_arguments: - keyword_arguments ratio: 0.8 mask_name: None single: False fundamental_matrics: fundamental_matrices: clean_keys: - ratio - symmetry keyword_arguments: - keyword_arguments method: reproj_threshold: confidence: subpixel_register: clean_keys: Loading @@ -37,14 +43,17 @@ subpixel_register: max_x_shift: 1.0 max_y_shift: 1.0 tiled: False keyword_arguments: - keyword_arguments upsampling: error_check: False suppress: clean_keys: - fundamental keyword_arguments: keyword_arguments min_radius: 2 k: 50 error_k: 0.1 cnet_conversion: clean_keys: Loading Loading
bin/image_match.py +9 −5 Original line number Diff line number Diff line import sys import os import argparse from autocnet.utils.utils import find_in_dict Loading @@ -13,10 +16,10 @@ def parse_arguments(): return args def match_images(args, config_dict): # print(find_in_dict(config_dict, 'to_isis')) # 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')) Loading Loading @@ -46,7 +49,7 @@ 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, 'suppress')['keyword_arguments']['k']) k=find_in_dict(config_dict, 'keyword_arguments')['k']) cnet = cg.to_cnet(clean_keys=find_in_dict(config_dict, 'cnet_conversion')['clean_keys'], isis_serials=True) Loading @@ -61,8 +64,9 @@ 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() command_line_args = parse_arguments() match_images(command_line_args, config) print(find_in_dict(config, 'fundamental_matrices')) # command_line_args = parse_arguments() # match_images(command_line_args, config)
image_match_config.yml +19 −10 Original line number Diff line number Diff line Loading @@ -13,18 +13,24 @@ match_features: # Any clean keys being passed in requires a method to have been used on the candidate graph object # before the key can be passed in ratio_checks: clean_keys: - keyword_arguments: - keyword_arguments ratio: 0.8 mask_name: None single: False fundamental_matrics: fundamental_matrices: clean_keys: - ratio - symmetry keyword_arguments: - keyword_arguments method: reproj_threshold: confidence: subpixel_register: clean_keys: Loading @@ -37,14 +43,17 @@ subpixel_register: max_x_shift: 1.0 max_y_shift: 1.0 tiled: False keyword_arguments: - keyword_arguments upsampling: error_check: False suppress: clean_keys: - fundamental keyword_arguments: keyword_arguments min_radius: 2 k: 50 error_k: 0.1 cnet_conversion: clean_keys: Loading