def update_track(det_frame, idd, det_bb, lst_det, frame):
"""
Cheecks if a bounding box is already labeled in the past 3 frames
or in the first 5 frames.
"""
n_past_frames = np.min([2,frame])
for past_frame in range(frame-n_past_frames, frame):
# If the past bb is labeled with 0 it is a removed bb on the remove_overlaps
past_frame_bb = [det_bb[i] for i,num in enumerate(lst_det) if (num == past_frame and det_bb[i][2]!=0)]
ious =[]
for i_past_frame_bb in past_frame_bb:
iou = bbox_iou(det_frame[3:7], i_past_frame_bb[3:7])
ious.append(iou)
if len(ious)==0:
continue
else:
arg_max = np.argmax(ious)
if np.max(ious)>=0.4:
det_frame[2] = past_frame_bb[arg_max][2]
past_frame_bb.pop(arg_max)
break
else:
continue
# We also check if the bb is in the first 5 frames as they are bg and they should
# appear in all the frames
mm = np.min([5,frame])
for bg_frame in range(0,mm):
bg_frame_bb = [det_bb[i] for i,num in enumerate(lst_det) if (num == bg_frame and det_bb[i][2]!=0)]
ious = []
for i_bg_frame_bb in bg_frame_bb:
iou = bbox_iou(det_frame[3:7], i_bg_frame_bb[3:7])
ious.append(iou)
if len(ious)==0:
continue
else:
arg_max = np.argmax(ious)
if np.max(ious)>=0.4:
det_frame[2] = bg_frame_bb[arg_max][2]
bg_frame_bb.pop(arg_max)
break
else:
continue
# If after checking with the past frames it still does not have a label then
# we consider it corresponds to a new track.
if det_frame[2] == 0:
det_frame[2] = idd
idd += 1
return det_frame, idd
def remove_overlaps(frame_n_bb):
# First we check if there are any overlaped detections and remove them
for i in range(0, len(frame_n_bb)):
length = len(frame_n_bb)
for j in range(i + 1, length):
if length == j:
break
iou = bbox_iou(frame_n_bb[i][3:7], frame_n_bb[j][3:7])
if iou > 0.9:
frame_n_bb.pop(j)
length = length - 1
return frame_n_bb
def remove_overlaps(frame_n_bb):
"""
This function detects if we have any overlapped detections, two bboxes for
the same object, and removes one.
"""
# First we check if there are any overlaped detections and remove them
for i in range(0, len(frame_n_bb)):
length = len(frame_n_bb)
for j in range(i+1, length):
if length == j:
break
iou = bbox_iou(frame_n_bb[i][3:7], frame_n_bb[j][3:7])
if iou > 0.9:
frame_n_bb.pop(j)
length = length - 1
return frame_n_bb
def animate_iou(dict_frame_gt_bb):
"""
Given a dictionary with frames and ground truth bounding boxes computes mean
IoU between the bounding boxes of each frame and the ground truth bounding
boxes with a gussian noise added.
Returns an animation of the evolution of mean IoU over time
"""
ious = []
for key, value in sorted(dict_frame_gt_bb.items(),
key=lambda x: int(x[0])):
value = [v[:-1] for v in value]
noisy_bb = add_noise_to_bbox(value, -5, 5)
iou = 0.0
for i, gt_bb in enumerate(value):
iou += bbox_iou([float(i) for i in gt_bb], noisy_bb[i])
ious.append(iou / len(value))
frames = list(range(0, len(ious)))
animation = plot_animation(frames, ious, "Frame", "IoU", [0, 1], 10)
return animation
def update_track_of(flow, det_frame, det_bb, idd, lst_det, frame):
"""
Moves a bb from the actual position to the position it occuied in the
past frame. If there is a bb with a large IoU we assign the same track value,
it not we create a new track value.
"""
xtl_1, ytl_1, xbr_1, ybr_1 = np.array(det_frame[3:7]).astype(int)
bb_flow = flow[ytl_1:ybr_1, xtl_1:xbr_1, :]
xtl = xtl_1 + np.mean(bb_flow[..., 0])
xbr = xbr_1 + np.mean(bb_flow[..., 0])
ytl = ytl_1 - np.mean(bb_flow[..., 1])
ybr = ybr_1 - np.mean(bb_flow[..., 1])
old_det = [xtl, ytl, xbr, ybr]
# If the past bb is labeled with 0 it is a removed bb on the remove_overlaps
past_frame_bb = [
det_bb[i] for i, num in enumerate(lst_det)
if (num == frame - 1 and det_bb[i][2] != 0)
]
ious = []
for i_past_frame_bb in past_frame_bb:
iou = bbox_iou(old_det, i_past_frame_bb[3:7])
ious.append(iou)
if len(ious) == 0:
pass
else:
arg_max = np.argmax(ious)
if np.max(ious) >= 0.7:
det_frame[2] = past_frame_bb[arg_max][2]
else:
pass
if det_frame[2] == 0:
det_frame[2] = idd
idd += 1
return det_frame, idd
