# -*- coding: utf-8 -*- """ Created on Fri Feb 23 11:04:48 2024 @author: ym """ import numpy as np import cv2 from scipy.spatial.distance import cdist # from trackers.utils import matching # TracksDict def readDict(boxes, TracksDict): feats = [] for i in range(boxes.shape[0]): tid, fid, bid = int(boxes[i, 4]), int(boxes[i, 7]), int(boxes[i, 8]) feat = TracksDict[f"frame_{fid}"]["feats"][bid] img = TracksDict[f"frame_{fid}"]["imgs"][bid] box = TracksDict[f"frame_{fid}"]["boxes"][bid] assert (box[:4].astype(int) == boxes[i, :4].astype(int)).all(), f"Please check: frame_{fid}" feats.append(feat) # img = TracksDict[fid][f'{bid}_img'] # cv2.imwrite(f'./data/imgs/{tid}_{fid}_{bid}.png', img) return np.asarray(feats, dtype=np.float32) def track_equal_track(atrack, btrack, TracksDict): # boxes: [x, y, w, h, track_id, score, cls, frame_index, box_index] # 0 1 2 3 4 5 6 7 8 aboxes = atrack.boxes bboxes = btrack.boxes ''' 1. 判断轨迹在时序上是否有交集 ''' afids = aboxes[:, 7].astype(np.int_) bfids = bboxes[:, 7].astype(np.int_) # 帧索引交集 interfid = set(afids).intersection(set(bfids)) # 或者直接判断帧索引是否有交集,返回 Ture or False # interfid = set(afids).isdisjoint(set(bfids)) if len(interfid): return False ''' 2. 轨迹特征相似度判断''' afeat = readDict(aboxes, TracksDict) bfeat = readDict(bboxes, TracksDict) feat = np.concatenate((afeat, bfeat), axis=0) emb_simil = 1-np.maximum(0.0, cdist(feat, feat, 'cosine')) emb_ = 1-cdist(np.mean(afeat, axis=0)[None, :], np.mean(bfeat, axis=0)[None, :], 'cosine') if emb_[0, 0]<0.66: return False ''' 3. 轨迹空间iou''' alabel = np.array([0] * afids.size, dtype=np.int_) blabel = np.array([1] * bfids.size, dtype=np.int_) label = np.concatenate((alabel, blabel), axis=0) fids = np.concatenate((afids, bfids), axis=0) indices = np.argsort(fids) idx_pair = [] for i in range(len(indices)-1): idx1, idx2 = indices[i], indices[i+1] if label[idx1] != label[idx2] and fids[idx2] - fids[idx1] <= 3: if label[idx1] == 0: a_idx = idx1 b_idx = idx2-alabel.size else: a_idx = idx2 b_idx = idx1-alabel.size idx_pair.append((a_idx, b_idx)) ious = [] for a, b in idx_pair: abox, bbox = aboxes[a, :], bboxes[b, :] xa1, ya1 = abox[0] - abox[2]/2, abox[1] - abox[3]/2 xa2, ya2 = abox[0] + abox[2]/2, abox[1] + abox[3]/2 xb1, yb1 = bbox[0] - bbox[2]/2, bbox[1] - bbox[3]/2 xb2, yb2 = bbox[0] + bbox[2]/2, bbox[1] + bbox[3]/2 inter = (np.minimum(xb2, xa2) - np.maximum(xb1, xa1)).clip(0) * \ (np.minimum(yb2, ya2) - np.maximum(yb1, ya1)).clip(0) # Union Area box1_area = abox[2] * abox[3] box2_area = bbox[2] * bbox[3] union = box1_area + box2_area - inter + 1e-6 ious.append(inter/union) cont = False if len(interfid) else True # cont2 = emb_[0, 0]>0.75 # cont3 = all(iou>0.5 for iou in ious) # cont = cont and cont2 and cont3 return cont def track_equal_str(atrack, btrack): if atrack == btrack: return True else: return False def merge_track(Residual): out_list = [] alist = [t for t in Residual] while alist: atrack = alist[0] cur_list = [] cur_list.append(atrack) alist.pop(0) blist = [b for b in alist] alist = [] for btrack in blist: if track_equal_str(atrack, btrack): cur_list.append(btrack) else: alist.append(btrack) out_list.append(cur_list) return out_list def main(): Residual = ['a', 'b', 'c', 'd', 'a', 'b', 'c', 'b', 'c', 'd'] out_list = merge_track(Residual) print(Residual) print(out_list) if __name__ == "__main__": main() # ============================================================================= # for i, atrack in enumerate(input_list): # cur_list = [] # cur_list.append(atrack) # del input_list[i] # # for j, btrack in enumerate(input_list): # if track_equal(atrack, btrack): # cur_list.append(btrack) # del input_list[j] # # out_list.append(cur_list) # =============================================================================