def _create_image_list(ref_images, image_list_path):
#create image list with coordinate of gps points
ills = []
for image in ref_images:
exif = opensfm_interface.load_exif(image_list_path + '/', image)
if ('gps' not in exif or 'latitude' not in exif['gps']
or 'longitude' not in exif['gps']):
logger.warning('Skipping {} because of missing GPS'.format(image))
continue
lat = exif['gps']['latitude']
lon = exif['gps']['longitude']
ills.append((image, lat, lon))
#print(ills)
create_image_list(ills, image_list_path)
def match_images(file_path, ref_images, cand_images, opensfm_config):
""" Perform pair matchings between two sets of images.
It will do matching for each pair (i, j), i being in
ref_images and j in cand_images, taking assumption that
matching(i, j) == matching(j ,i). This does not hold for
non-symmetric matching options like WORDS. Data will be
stored in i matching only.
"""
# Get EXIFs data
print('matching images before exif')
all_images = list(set(ref_images+cand_images))
print('matching images right before load exif')
exifs = {im: opensfm_interface.load_exif(file_path,im) for im in all_images}
print('matching images after')
# Generate pairs for matching
# generate pairs for matching
# list of tuples
pairs, preport = new_pairs_selection.match_candidates_from_metadata( file_path,
ref_images, cand_images, exifs, opensfm_config)
#print('printing pairs')
#print(pairs)
#print()
#print()
#exit(1)
# Match them !
print('match images now')
ret = match_images_with_pairs(file_path ,opensfm_config, exifs, ref_images, pairs), preport
#print('ret')
#print(ret)
#print()
#print()
#exit(1)
print('finish match and returning')
return ret
def match_images(file_path, ref_images, cand_images, opensfm_config):
""" Perform pair matchings between two sets of images.
It will do matching for each pair (i, j), i being in
ref_images and j in cand_images, taking assumption that
matching(i, j) == matching(j ,i). This does not hold for
non-symmetric matching options like WORDS. Data will be
stored in i matching only.
"""
# Get EXIFs data
all_images = list(set(ref_images + cand_images))
exifs = {
im: opensfm_interface.load_exif(file_path, im)
for im in all_images
}
# Generate pairs for matching
pairs, preport = new_pairs_selection.match_candidates_from_metadata(
file_path, ref_images, cand_images, exifs, opensfm_config)
# Match them !
return match_images_with_pairs(file_path, opensfm_config, exifs,
ref_images, pairs), preport
#job_queue.join()
start = timer()
print('after queue join filepath')
ref_images = os.listdir(file_path +'/images')
print(ref_images)
cand_images = ref_images
exifs = {im: opensfm_interface.load_exif(file_path,im) for im in ref_images}
print(exifs)
print(file_path)
pairs, preport = new_pairs_selection.match_candidates_from_metadata( file_path,
ref_images, cand_images, exifs, opensfm_config)
print('here')
print(pairs)
results = {}
#for each pair