def load_annotations(self):
assert self.data_type == "mot"
gt_filename = os.path.join(self.data_root, self.seq_name, "gt", "gt.txt")
self.gt_frame_dict = read_results(gt_filename, self.data_type, is_gt=True)
self.gt_ignore_frame_dict = read_results(
gt_filename, self.data_type, is_ignore=True
)
def load_annotations(self): # 读取了两种数据，第二种方式忽略了一部分行人框
assert self.data_type == 'mot'
gt_filename = os.path.join(self.data_root, self.seq_name, 'gt',
'gt.txt')
self.gt_frame_dict = read_results(gt_filename,
self.data_type,
is_gt=True) # 加载ground truth，
self.gt_ignore_frame_dict = read_results(gt_filename,
self.data_type,
is_ignore=True)
def load_annotations(self):
assert self.data_type == 'mot'
gt_filename = os.path.join(self.data_root, self.seq_name, 'gt',
'gt.txt')
print('gt_filename', gt_filename)
self.gt_frame_dict = read_results(gt_filename,
self.data_type,
is_gt=True)
self.gt_ignore_frame_dict = read_results(gt_filename,
self.data_type,
is_ignore=True)
def load_annotations(self):
assert self.data_type == 'mot'
gt_filename = os.path.join(self.data_root, self.seq_name, 'gt',
'gt.txt')
self.gt_frame_dict = read_results(gt_filename,
self.data_type,
is_gt=True)
self.gt_ignore_frame_dict = read_results(gt_filename,
self.data_type,
is_ignore=True)
if not os.path.exists(gt_filename):
print('gt file not found, empty gt assumed.')
else:
print('len %d loaded from gt' % len(self.gt_frame_dict))
def eval_file(self, filename):
self.reset_accumulator()
result_frame_dict = read_results(filename, self.data_type, is_gt=False)
#frames = sorted(list(set(self.gt_frame_dict.keys()) | set(result_frame_dict.keys())))
frames = sorted(list(set(result_frame_dict.keys())))
for frame_id in frames:
trk_objs = result_frame_dict.get(frame_id, [])
trk_tlwhs, trk_ids = unzip_objs(trk_objs)[:2]
self.eval_frame(frame_id, trk_tlwhs, trk_ids, rtn_events=False)
return self.acc
def eval_file(self, filename):
self.reset_accumulator()
result_frame_dict = read_results(filename, self.data_type,
is_gt=False) # 加载检测结果
frames = sorted(
list(
set(self.gt_frame_dict.keys())
| set(result_frame_dict.keys()))) # 帧的并集
for frame_id in frames:
trk_objs = result_frame_dict.get(frame_id, [])
trk_tlwhs, trk_ids = unzip_objs(trk_objs)[:2] # 预测track中的边框、id
self.eval_frame(frame_id, trk_tlwhs, trk_ids,
rtn_events=False) # 用于和ground truth进行计算
return self.acc
def eval_file(self, filename):
self.reset_accumulator()
if self.return_fn and self.return_fp:
fns = {}
fps = {}
matched = {}
fp_confs = {}
result_frame_dict = read_results(filename, self.data_type, is_gt=False)
frames = sorted(
list(
set(self.gt_frame_dict.keys())
| set(result_frame_dict.keys())))
for frame_id in frames:
trk_objs = result_frame_dict.get(frame_id, [])
trk_tlwhs, trk_ids, trk_confs = unzip_objs(trk_objs)
trk_confs = np.array(trk_confs)
if self.return_fn and self.return_fp:
_, oids_masked, hids_masked = self.eval_frame(frame_id,
trk_tlwhs,
trk_ids,
rtn_events=False)
gt_objs = self.gt_frame_dict.get(frame_id, [])
gt_tlwhs, gt_ids = unzip_objs(gt_objs)[:2]
# These are the matched boxes
matched[frame_id] = {}
matched[frame_id]['gt'] = gt_tlwhs[oids_masked]
matched[frame_id]['trk'] = trk_tlwhs[hids_masked]
matched[frame_id]['trk_confs'] = trk_confs[hids_masked]
# FN FP
fns[frame_id] = gt_tlwhs[~oids_masked]
fps[frame_id] = trk_tlwhs[~hids_masked]
fp_confs[frame_id] = trk_confs[~hids_masked]
else:
self.eval_frame(frame_id, trk_tlwhs, trk_ids, rtn_events=False)
if self.return_fn and self.return_fp:
return self.acc, fns, fps, matched, fp_confs
return self.acc
