def index_at_multiple_scales(
codebook_dir,
min_scale,
max_scale,
height_aspect,
width_aspect,
vectorization_factor=1,
precompute_target=None,
use_stabilization=True,
stabilization_threshold=0.85,
randomness=0.0,
caching=True,
use_detect_faces=True,
):
scale2index = {}
scale2mosaic = {}
count = 0
scales = range(min_scale, max_scale + 1, 1)
aspect_ratio = height_aspect / float(width_aspect)
with tqdm(total=len(scales)) as pbar:
for scale in scales:
print("Indexing scale=%d..." % scale)
h, w = compute_hw(scale, height_aspect, width_aspect)
tile_index, _, tile_images = index_images(
paths='%s/*.jpg' % codebook_dir,
aspect_ratio=aspect_ratio,
height=h,
width=w,
vectorization_scaling_factor=vectorization_factor,
caching=True,
use_detect_faces=use_detect_faces,
)
scale2index[scale] = (tile_index, tile_images)
# then precompute the mosaic
h, w = compute_hw(scale, height_aspect, width_aspect)
# mosaic-ify & show it
if precompute_target is not None:
mosaic, _, _ = mosaicify(
precompute_target,
h,
w,
tile_index,
tile_images,
use_stabilization=use_stabilization,
stabilization_threshold=stabilization_threshold,
randomness=randomness)
scale2mosaic[scale] = mosaic
count += 1
pbar.update(1)
return scale2index, scale2mosaic
# constants
height_aspect = 4
width_aspect = 3
target_image = cv2.imread(args.target)
# index
scale2index = {}
scales = range(args.min_scale, args.max_scale + 1, 1)
dimensions = []
global_timings = defaultdict(list)
num_tiles = []
for scale in scales:
print("Indexing scale=%d..." % scale)
h, w = compute_hw(scale, height_aspect, width_aspect)
tile_index, _, tile_images = index_images(
paths='%s/*.jpg' % args.codebook_dir,
aspect_ratio=height_aspect / float(width_aspect),
height=h,
width=w,
caching=True,
)
scale2index[scale] = (tile_index, tile_images)
# then precompute the mosaic
h, w = compute_hw(scale, height_aspect, width_aspect)
dims = h * w * 3
# mosaic-ify & show it
_, rect_starts, timings = mosaicify(target_image,