match_dict = associate.read_file_list(match_text)
groundtruth_dict = associate.read_file_list(groundtruth_text)
rgb_folder_full = dataset_root + rgb_folder
depth_folder_full = dataset_root + depth_folder
rgb_files = ListGenerator.get_files_from_directory(rgb_folder_full,
delimiter='.')
depth_files = ListGenerator.get_files_from_directory(depth_folder_full,
delimiter='.')
rgb_file_total = len(rgb_files)
depth_file_total = len(depth_files)
#image_groundtruth_dict = dict(associate.match(rgb_text, groundtruth_text,max_difference=0.2,with_duplicates=True))
image_groundtruth_dict = dict(associate.match(rgb_text,
groundtruth_text)) #f1_d2
parameters = data_file.split('_')
if data_file_2:
parameters_2 = data_file_2.split('_')
if data_file_3:
parameters_3 = data_file_3.split('_')
if data_file_4:
parameters_4 = data_file_4.split('_')
start_idx = float(parameters[0])
max_count = int(parameters[9])
offset = int(parameters[10])
#max_its = int(parameters[1])
#eps = float(parameters[2])
#bench_path = '/Users/marchaubenstock/Workspace/Diplomarbeit_Resources/rccar_15_11_18/'
#bench_path = '/Users/marchaubenstock/Workspace/Diplomarbeit_Resources/rccar_26_09_18/'
bench_path = '/Users/marchaubenstock/Workspace/Diplomarbeit_Resources/VO_Bench/'
dataset = 'rgbd_dataset_freiburg2_desk/'
#rgb_text = bench_path + dataset + 'rgb_rect.txt'
#depth_text = bench_path + dataset + 'depth_large_rect_norm.txt'
#match_file = bench_path + dataset + 'matches_rect_with_duplicates_norm.txt'
rgb_text = bench_path + dataset + 'rgb.txt'
depth_text = bench_path + dataset + 'accelerometer.txt'
match_file = bench_path + dataset + 'accelerometer_rgb_matches.txt'
with_duplicates_for_steering = True
matches = associate.match(rgb_text,depth_text,with_duplicates=with_duplicates_for_steering,max_difference=0.2)
try:
os.remove(match_file)
except OSError:
pass
with open(match_file, 'w') as f:
f.write('# rgb_timestamp depth_timesamp\n')
for (rgb_ts,depth_ts) in matches:
rgb_ts_string = f'{rgb_ts:.9f}'
depth_ts_string = f'{depth_ts:.9f}'
f.write("%s %s\n" % (rgb_ts_string,depth_ts_string))
groundtruth_dict = associate.read_file_list(groundtruth_text)
rgb_folder_full = dataset_root + rgb_folder
depth_folder_full = dataset_root + depth_folder
rgb_files = ListGenerator.get_files_from_directory(rgb_folder_full,
delimiter='.')
depth_files = ListGenerator.get_files_from_directory(depth_folder_full,
delimiter='.')
rgb_file_total = len(rgb_files)
depth_file_total = len(depth_files)
image_groundtruth_dict = dict(
associate.match(rgb_text,
groundtruth_text,
with_duplicates=True,
max_difference=0.3))
rgb_encoder_dict = associate.read_file_list(rgb_encoder_text)
encoder_dict = associate.read_file_list(encoder_text)
parameters = data_file.split('_')
if data_file_2:
parameters_2 = data_file_2.split('_')
if data_file_3:
parameters_3 = data_file_3.split('_')
if data_file_4:
parameters_4 = data_file_4.split('_')
start_idx = float(parameters[0])
max_count = int(parameters[9])
offset = int(parameters[10])
+ '_' + f"{alpha_step}" \
+ '_' + f"{image_range_offset_start}" \
+ '_' + f"{use_ndc}" \
+ '_' + f"{use_robust}" \
+ '_' + f"{use_motion_prior}" \
+ '_' + f"{use_ackermann}" \
+ '_' + f"{max_count}" \
+ '_' + f"{offset}"
if additional_info:
info += '_' + additional_info
acceleration_list = []
match_dict = associate.read_file_list(match_text)
image_groundtruth_dict = dict(associate.match(rgb_text, groundtruth_text, max_difference=0.2,with_duplicates=True))
rgb_acceleration_dict = associate.read_file_list(acceleration_match)
acceleration_dict = associate.read_file_list(acceleration_text)
post_process_gt = PostProcessGroundTruth.PostProcessTUM_F2()
print(name+'_'+info+'\n')
start = ListGenerator.get_index_of_id(start_idx,rgb_files)
ref_id_list, target_id_list, ref_files_failed_to_load = ListGenerator.generate_files_to_load_match(
rgb_files,
start=start,
max_count=max_count,
offset=offset,
ground_truth_dict=image_groundtruth_dict,
from Benchmark import associate
import os
bench_path = '/Users/marchaubenstock/Workspace/Diplomarbeit_Resources/VO_Bench/'
xyz_dataset = 'rgbd_dataset_freiburg1_xyz/'
rgb_folder = 'rgb/'
depth_folder = 'depth/'
rgb_text = bench_path+xyz_dataset+'rgb.txt'
depth_text = bench_path+xyz_dataset+'depth.txt'
matches = associate.match(rgb_text,depth_text)
match_file = bench_path+xyz_dataset+'matches.txt'
try:
os.remove(match_file)
except OSError:
pass
with open(match_file, 'w') as f:
f.write('# rgb_timestamp depth_timestamp\n')
for (rgb_ts,depth_ts) in matches:
f.write("%s %s\n" % (rgb_ts,depth_ts))
