log_level=logging.INFO)
continue
layer_num = get_layer_num(sec_num, args.initial_layer_num,
args.reverse, max_sec_num)
sec_relevant_mfovs = None
if filtered_mfovs_map is not None:
if (wafer_num, sec_num) not in filtered_mfovs_map:
logger.report_event(
"WARNING: cannot find filtered data for (wafer, sec): {}, skipping"
.format((wafer_num, sec_num)),
log_level=logging.INFO)
continue
sec_relevant_mfovs = filtered_mfovs_map[wafer_num, sec_num]
res = pool.apply_async(create_and_save_single_section,
(sec_relevant_mfovs, sections_map[sec_num],
layer_num, args.wafer_folder, out_ts_fname))
pool_results.append(res)
for res in pool_results:
res.get()
if __name__ == '__main__':
args = parse_args()
logger.start_process('main', 'create_tilespecs.py', [args])
create_tilespecs(args)
logger.end_process('main ending', rh_logger.ExitCode(0))
with in_fs.open(fs.path.basename(in_ts_fname), 'rt') as in_f:
in_ts = ujson.load(in_f)
wafer_num = int(
fs.path.basename(in_ts_fname).split('_')[0].split('W')[1])
sec_num = int(
fs.path.basename(in_ts_fname).split('.')[0].split('_')[1].split(
'Sec')[1])
section = Section.create_from_tilespec(in_ts,
wafer_section=(wafer_num,
sec_num))
stitcher.stitch_section(section)
# Save the tilespec
section.save_as_json(out_ts_fname)
# out_tilespec = section.tilespec
# import json
# with open(out_ts_fname, 'wt') as out_f:
# json.dump(out_tilespec, out_f, sort_keys=True, indent=4)
del stitcher
if __name__ == '__main__':
args = parse_args()
logger.start_process('main', '2d_stitcher_driver.py', [args])
run_stitcher(args)
logger.end_process('main ending', rh_logger.ExitCode(0))
'tile_files_or_dirs',
metavar='tile_files_or_dirs',
type=str,
nargs='+',
help=
'a list of json files that need to be normalized or a directories of json files'
)
parser.add_argument('-o',
'--output_dir',
type=str,
help='an output directory (default: ./after_norm)',
default='./after_norm')
parser.add_argument('-p',
'--processes_num',
type=int,
help='number of processes (default: 1)',
default=1)
args = parser.parse_args()
logger.start_process('normalize_coordinates', 'normalize_coordinates.py',
[args.tile_files_or_dirs, args.output_dir])
pool = mp.Pool(processes=args.processes_num)
normalize_coordinates(args.tile_files_or_dirs, args.output_dir, pool)
pool.close()
pool.join()
logger.end_process('normalize_coordinates', rh_logger.ExitCode(0))
# stitcher.stitch_section(section) # will stitch and update the section
#
# # Save the transforms to file
# import json
# print('Writing output to: {}'.format(out_fname))
# section.save_as_json(out_fname)
# # img_fnames, imgs = StackAligner.read_imgs(imgs_dir)
# # for img_fname, img, transform in zip(img_fnames, imgs, transforms):
# # # assumption: the output image shape will be the same as the input image
# # out_fname = os.path.join(out_path, os.path.basename(img_fname))
# # img_transformed = cv2.warpAffine(img, transform[:2,:], (img.shape[1], img.shape[0]), flags=cv2.INTER_AREA)
# # cv2.imwrite(out_fname, img_transformed)
# Testing
# test_detector('/n/home10/adisuis/Harvard/git/rh_aligner/tests/ECS_test9_cropped/images/010_S10R1', conf_fname, 8, 500)
logger.start_process('main', 'stitcher.py', [section_dir, conf_fname])
section = ThumbnailsSection.create_from_full_thumbnail_coordinates(
section_dir, section_num, processes_num=processes_num)
conf = Stitcher.load_conf_from_file(conf_fname)
stitcher = Stitcher(conf)
stitcher.stitch_section(
section) # will stitch and update the section tiles' transformations
# render the stitched section
ds_rate = 1.0 / 8
render_section(out_jpg_fname, section, ds_rate)
# TODO - output the section
logger.end_process('main ending', rh_logger.ExitCode(0))
2].T + noiseA
transformB = np.array([[np.cos(50), -np.sin(50), 600],
[np.sin(50), np.cos(50), 250], [0., 0., 1.]])
ptsB_1 = np.random.uniform(0, 800, ((100, 2)))
noiseB = np.random.uniform(-7, 7, ptsB_1.shape)
ptsB_2 = np.dot(ptsB_1, transformB[:2, :2].T) + transformB[:2,
2].T + noiseB
# Add outliers
ptsC_1 = np.random.uniform(0, 800, ((5, 2)))
noiseC = np.random.uniform(-3, 3, ptsC_1.shape)
ptsC_2 = ptsC_1 + noiseC
# stack the matches
pts1 = np.vstack((ptsA_1, ptsB_1, ptsC_1))
pts2 = np.vstack((ptsA_2, ptsB_2, ptsC_2))
logger.start_process('main', 'affine_transforms_grouper.py', [])
# create the clusterer
grouper = AffineTransformsGrouper()
groups_masks, outlier_mask = grouper.group_matches(pts1, pts2)
print("Found {} groups masks".format(len(groups_masks)))
for gm_idx, gm in enumerate(groups_masks):
print("Group masks {}: size:{}".format(gm_idx, np.sum(gm)))
print("Found {} outlier matches".format(np.sum(outlier_mask)))
logger.end_process('main ending', rh_logger.ExitCode(0))
# TODO - Should be done in a parallel fashion
for ts_fname in secs_ts_fnames:
with open(ts_fname, 'rt') as in_f:
tilespec = ujson.load(in_f)
wafer_num = int(os.path.basename(ts_fname).split('_')[0].split('W')[1])
sec_num = int(
os.path.basename(ts_fname).split('.')[0].split('_')[1].split('Sec')
[1])
sections.append(
Section.create_from_tilespec(tilespec,
wafer_section=(wafer_num, sec_num)))
logger.report_event("Initializing aligner", log_level=logging.INFO)
aligner = StackAligner(conf)
logger.report_event("Aligning sections", log_level=logging.INFO)
aligner.align_sections(
sections) # will align and update the section tiles' transformations
del aligner
logger.end_process('main ending', rh_logger.ExitCode(0))
if __name__ == '__main__':
args = parse_args()
logger.start_process('main', 'align_3d_tilespecs_list.py', [args])
run_aligner(args)
logger.end_process('main ending', rh_logger.ExitCode(0))
args.output_dir, 'W{}_Sec{}_montaged.json'.format(
str(wafer_num).zfill(2),
str(sec_num).zfill(3)))
if os.path.exists(out_ts_fname):
continue
layer_num = get_layer_num(sec_num, args.initial_layer_num)
print("Stitching {}".format(sec_dir))
section = Section.create_from_full_image_coordinates(
os.path.join(sec_dir, 'full_image_coordinates.txt'), layer_num)
stitcher.stitch_section(section)
# Save the tilespec
section.save_as_json(out_ts_fname)
# out_tilespec = section.tilespec
# import json
# with open(out_ts_fname, 'wt') as out_f:
# json.dump(out_tilespec, out_f, sort_keys=True, indent=4)
del stitcher
if __name__ == '__main__':
args = parse_args()
logger.start_process('main', 'stitch_2d_raw_folders_list.py', [args])
run_stitcher(args)
logger.end_process('main ending', rh_logger.ExitCode(0))
if __name__ == '__main__':
secs_ts_fnames = [
'/n/home10/adisuis/Harvard/git_lichtmangpu01/mb_aligner/scripts/ECS_test9_cropped_010_S10R1.json',
'/n/home10/adisuis/Harvard/git_lichtmangpu01/mb_aligner/scripts/ECS_test9_cropped_011_S11R1.json',
'/n/home10/adisuis/Harvard/git_lichtmangpu01/mb_aligner/scripts/ECS_test9_cropped_012_S12R1.json',
'/n/home10/adisuis/Harvard/git_lichtmangpu01/mb_aligner/scripts/ECS_test9_cropped_013_S13R1.json',
'/n/home10/adisuis/Harvard/git_lichtmangpu01/mb_aligner/scripts/ECS_test9_cropped_014_S14R1.json'
]
out_folder = './output_aligned_ECS_test9_cropped'
conf_fname = '../../conf/conf_example.yaml'
logger.start_process('main', 'aligner.py', [secs_ts_fnames, conf_fname])
conf = StackAligner.load_conf_from_file(conf_fname)
logger.report_event("Loading sections", log_level=logging.INFO)
sections = []
# TODO - Should be done in a parallel fashion
for ts_fname in secs_ts_fnames:
with open(ts_fname, 'rt') as in_f:
tilespec = ujson.load(in_f)
wafer_num = 1
sec_num = int(os.path.basename(ts_fname).split('_')[-1].split('S')[1].split('R')[0])
sections.append(Section.create_from_tilespec(tilespec, wafer_section=(wafer_num, sec_num)))
logger.report_event("Initializing aligner", log_level=logging.INFO)
aligner = StackAligner(conf)
logger.report_event("Aligning sections", log_level=logging.INFO)
aligner.align_sections(sections) # will align and update the section tiles' transformations
log_level=logging.WARN)
missing_sections = [
i for i in range(1, max(sorted_sec_keys)) if i not in sections_map
]
logger.report_event("Missing sections: {}".format(missing_sections),
log_level=logging.WARN)
logger.report_event("Outputing sections to list to: {}".format(
args.output_file),
log_level=logging.INFO)
with open(args.output_file, 'wt') as out_f:
for sec_num in sorted_sec_keys:
if isinstance(sections_map[sec_num], list):
folder_name = os.sep.join(
sections_map[sec_num][0].split(os.sep)[:-2]
) # strip the mfov path, and the coordinates file name
else:
folder_name = os.sep.join(sections_map[sec_num].split(
os.sep)[:-1]) # strip the coordinates file name
out_f.write(folder_name)
out_f.write('\n')
if __name__ == '__main__':
args = parse_args()
logger.start_process('main', 'create_raw_folders_list.py', [args])
create_raw_folders_list(args)
logger.end_process('main ending', rh_logger.ExitCode(0))
@staticmethod
def align_img_files(imgs_dir, conf, processes_num):
# Read the files
_, imgs = StackAligner.read_imgs(imgs_dir)
aligner = StackAligner(conf, processes_num)
return aligner.align_imgs(imgs)
if __name__ == '__main__':
imgs_dir = '/n/coxfs01/paragt/Adi/R0/images_margin'
conf_fname = '../conf_example.yaml'
out_path = './output_imgs'
processes_num = 8
logger.start_process('main', 'aligner.py',
[imgs_dir, conf_fname, out_path, processes_num])
conf = StackAligner.load_conf_from_file(conf_fname)
transforms = StackAligner.align_img_files(imgs_dir, conf, processes_num)
# Save the transforms to a temp output folder
if not os.path.exists(out_path):
os.makedirs(out_path)
print('Writing output to: {}'.format(out_path))
img_fnames, imgs = StackAligner.read_imgs(imgs_dir)
for img_fname, img, transform in zip(img_fnames, imgs, transforms):
# assumption: the output image shape will be the same as the input image
out_fname = os.path.join(out_path, os.path.basename(img_fname))
img_transformed = cv2.warpAffine(img,
transform[:2, :],
(img.shape[1], img.shape[0]),
parser.add_argument("-s",
"--sec_num",
metavar="sec_num",
type=int,
help="The section number. (default: 1)",
default=1)
return parser.parse_args(args)
def run_stitcher(args):
# Make up a section number
section = Section.create_from_full_image_coordinates(
args.images_coords_file, args.sec_num)
conf = Stitcher.load_conf_from_file(args.conf_fname)
stitcher = Stitcher(conf)
stitcher.stitch_section(section) # will stitch and update the section
# Save the transforms to file
print('Writing output to: {}'.format(args.output_json))
section.save_as_json(args.output_json)
if __name__ == '__main__':
args = parse_args()
logger.start_process('main', 'stitch_2d.py', [args])
run_stitcher(args)
logger.end_process('main ending', rh_logger.ExitCode(0))