def check_gradients():
log_file = open('datasets/synth_street_small/gradients.txt', 'w+')
img_range = range(10, 11)
for key_img in img_range:
info = 'Key: ' + str(key_img) + '\n'
log_file.write(info)
print(info + '\n')
ref_img = key_img + 1
runner = RUNNER.Runner(stereo_pair_builder, runtime_settings, key_img, [ref_img], root_dir)
runner.check_gradient(log_file, post_process=True, debug_mode=False, skip_guards=False)
log_file.close()
def bulk_run():
log_file = open('datasets/ipad_small/log_file.txt', 'w+')
img_range = range(361, 800)
for key_img in img_range:
info = 'Key: ' + str(key_img) + '\n'
print(info + '\n')
log_file.write(info)
ref_img = key_img + 1
runner = RUNNER.Runner(stereo_pair_builder, runtime_settings, key_img,
[ref_img], root_dir)
runner.run_check_pixels(log_file,
post_process=True,
debug_mode=False,
skip_guards=True)
log_file.close()
image_loader = IMAGE_LOADER.ImageLoader(root_dir + dataset + type + sequence +
images_dir)
vo = VO_PARSER.VoParserSynth(root_dir, dataset + type + sequence + odom_path)
runtime_settings = SETTINGS.Settings(
10, 0.0001, 0.9, 5, 0.05,
-1.0) # -1.0 for z (or general motion eq.) TODO investigate
ref_count = 8
step = 1
ref_list = []
for count in range(step, ref_count + 1, step):
ref_list.append(key + count)
stereo_pair_builder = STEREO_PAIR_BUILDER.StereoPairBuilder(
cm, image_loader, vo, 0, runtime_settings)
runner = RUNNER.Runner(stereo_pair_builder, runtime_settings, key, ref_list,
root_dir)
# ground_truth = POST.Evaluation.load_ground_truth(depth_file, 424, 512,flip_across_y=True)
# inverted_ground_truth = POST.Evaluation.calc_inverse_ground_truth(ground_truth, runtime_settings,max_thresh=2500,isIpad=True)
inverted_ground_truth = None
# VISUALIZE.show_frame(inverted_ground_truth, runtime_settings, path=root_dir, name='ground_truth', cmap='nipy_spectral')
runner.run(VISUALIZE.visualize_enum.SHOW_DEPTH,
inverted_ground_truth,
normalize=True,
calc_error_metrics=False,
post_process=True,
regularize=True,
show_frame=True,
debug_mode=False,
skip_guards=True)