Spaces:
Sleeping
Sleeping
# Copyright (C) 2024-present Naver Corporation. All rights reserved. | |
# Licensed under CC BY-NC-SA 4.0 (non-commercial use only). | |
# | |
# -------------------------------------------------------- | |
# utilities needed to load image pairs | |
# -------------------------------------------------------- | |
import numpy as np | |
import torch | |
def make_pairs(imgs, scene_graph='complete', prefilter=None, symmetrize=True): | |
pairs = [] | |
if scene_graph == 'complete': # complete graph | |
for i in range(len(imgs)): | |
for j in range(i): | |
pairs.append((imgs[i], imgs[j])) | |
elif scene_graph.startswith('swin'): | |
winsize = int(scene_graph.split('-')[1]) if '-' in scene_graph else 3 | |
pairsid = set() | |
for i in range(len(imgs)): | |
for j in range(1, winsize+1): | |
idx = (i + j) % len(imgs) # explicit loop closure | |
pairsid.add((i, idx) if i < idx else (idx, i)) | |
for i, j in pairsid: | |
pairs.append((imgs[i], imgs[j])) | |
elif scene_graph.startswith('oneref'): | |
refid = int(scene_graph.split('-')[1]) if '-' in scene_graph else 0 | |
for j in range(len(imgs)): | |
if j != refid: | |
pairs.append((imgs[refid], imgs[j])) | |
elif scene_graph.startswith('prev'): | |
for i in range(1, len(imgs)): | |
for j in range(i): | |
pairs.append((imgs[j], imgs[i])) | |
if symmetrize: | |
pairs += [(img2, img1) for img1, img2 in pairs] | |
# now, remove edges | |
if isinstance(prefilter, str) and prefilter.startswith('seq'): | |
pairs = filter_pairs_seq(pairs, int(prefilter[3:])) | |
if isinstance(prefilter, str) and prefilter.startswith('cyc'): | |
pairs = filter_pairs_seq(pairs, int(prefilter[3:]), cyclic=True) | |
return pairs | |
def sel(x, kept): | |
if isinstance(x, dict): | |
return {k: sel(v, kept) for k, v in x.items()} | |
if isinstance(x, (torch.Tensor, np.ndarray)): | |
return x[kept] | |
if isinstance(x, (tuple, list)): | |
return type(x)([x[k] for k in kept]) | |
def _filter_edges_seq(edges, seq_dis_thr, cyclic=False): | |
# number of images | |
n = max(max(e) for e in edges)+1 | |
kept = [] | |
for e, (i, j) in enumerate(edges): | |
dis = abs(i-j) | |
if cyclic: | |
dis = min(dis, abs(i+n-j), abs(i-n-j)) | |
if dis <= seq_dis_thr: | |
kept.append(e) | |
return kept | |
def filter_pairs_seq(pairs, seq_dis_thr, cyclic=False): | |
edges = [(img1['idx'], img2['idx']) for img1, img2 in pairs] | |
kept = _filter_edges_seq(edges, seq_dis_thr, cyclic=cyclic) | |
return [pairs[i] for i in kept] | |
def filter_edges_seq(view1, view2, pred1, pred2, seq_dis_thr, cyclic=False): | |
edges = [(int(i), int(j)) for i, j in zip(view1['idx'], view2['idx'])] | |
kept = _filter_edges_seq(edges, seq_dis_thr, cyclic=cyclic) | |
print(f'>> Filtering edges more than {seq_dis_thr} frames apart: kept {len(kept)}/{len(edges)} edges') | |
return sel(view1, kept), sel(view2, kept), sel(pred1, kept), sel(pred2, kept) | |