def ious(atlbrs, btlbrs):
"""
Compute cost based on IoU
:type atlbrs: list[tlbr] | np.ndarray
:type atlbrs: list[tlbr] | np.ndarray
:rtype ious np.ndarray
"""
ious = np.zeros((len(atlbrs), len(btlbrs)), dtype=np.float)
if ious.size == 0:
return ious
ious = bbox_ious(
np.ascontiguousarray(atlbrs, dtype=np.float),
np.ascontiguousarray(btlbrs, dtype=np.float)
)
return ious
def ious(atlbrs, btlbrs):
"""Compute cost based on IoU
Arguments:
atlbrs: np.array, list of boxes
btlbrs: np.array, list of boxes
Returns:
ious: np.array, matrix of IoUs between each box
Raises:
"""
ious = np.zeros((len(atlbrs), len(btlbrs)), dtype=np.float)
if ious.size == 0:
return ious
ious = bbox_ious(
np.ascontiguousarray(atlbrs, dtype=np.float),
np.ascontiguousarray(btlbrs, dtype=np.float),
)
return ious
def visualize_comparison(dataroot,
seq,
save_dir,
result_dir_1,
result_dir_2,
compile_images_only=False):
import pandas as pd
from cython_bbox import bbox_overlaps as bbox_ious
from tracker import matching
from tracking_utils import visualization as vis
res_1 = pd.read_csv(osp.join(result_dir_1, f"{seq}.txt"),
sep=',',
names=[
'frame', 'id', 'left', 'top', 'width', 'height',
'conf', 'misc1', 'misc2', 'misc3'
])
res_2 = pd.read_csv(osp.join(result_dir_2, f"{seq}.txt"),
sep=',',
names=[
'frame', 'id', 'left', 'top', 'width', 'height',
'conf', 'misc1', 'misc2', 'misc3'
])
img_root = osp.join(dataroot, seq, 'img1')
save_root_1 = osp.join(osp.abspath(save_dir), osp.basename(result_dir_1),
seq)
os.makedirs(save_root_1, exist_ok=True)
save_root_2 = osp.join(osp.abspath(save_dir), osp.basename(result_dir_2),
seq)
os.makedirs(save_root_2, exist_ok=True)
if not compile_images_only:
# for frame in np.unique(res_1['frame']):
for frame in range(np.min(res_1['frame']), np.max(res_1['frame'])):
# if frame == 250:
# break
res_1_frame = res_1[res_1['frame'] == frame]
res_2_frame = res_2[res_2['frame'] == frame]
res_1_boxes_np = np.array(
res_1_frame[['left', 'top', 'width', 'height']])
res_1_boxes_np[:, 2:] += res_1_boxes_np[:, :2]
res_2_boxes_np = np.array(
res_2_frame[['left', 'top', 'width', 'height']])
res_2_boxes_np[:, 2:] += res_2_boxes_np[:, :2]
img1 = cv2.imread(osp.join(img_root, f"{frame:06d}.jpg"))
img2 = cv2.imread(osp.join(img_root, f"{frame:06d}.jpg"))
if res_1_boxes_np.shape[0] > 0 and res_2_boxes_np.shape[0] > 0:
iou = bbox_ious(res_1_boxes_np, res_2_boxes_np)
matches, u_res_1, u_res_2 = matching.linear_assignment(
-iou, thresh=-0.7)
if len(matches) > 0:
# Plot the matchings in normal colors
matches_res_1 = res_1_frame.iloc[matches[:, 0]]
matches_res_2 = res_2_frame.iloc[matches[:, 1]]
# matches_res_2['id'].iloc[matches[:, 1]] = matches_res_1['id'].iloc[matches[:, 0]]
online_ids = matches_res_1['id'].to_list()
# online_ids = matches_res_2['id'].to_list()
matches_res_1_np = np.array(
matches_res_1[['left', 'top', 'width', 'height']])
matches_res_2_np = np.array(
matches_res_2[['left', 'top', 'width', 'height']])
online_im_1 = vis.plot_tracking(img1,
matches_res_1_np,
online_ids,
frame_id=frame,
fps=-1,
line_thickness=1)
online_im_2 = vis.plot_tracking(img2,
matches_res_2_np,
online_ids,
frame_id=frame,
fps=-1,
line_thickness=1)
else:
online_im_1 = img1
online_im_2 = img2
# ipdb.set_trace()
# Plot the unmatched in thicker colors
unmatches_res_1 = res_1_frame.iloc[u_res_1]
unmatches_res_1_np = np.array(
unmatches_res_1[['left', 'top', 'width', 'height']])
if len(unmatches_res_1) > 0:
if len(unmatches_res_1.shape) == 1:
unmatched_res_1_ids = [unmatches_res_1['id']]
scores = [unmatches_res_1['conf']]
unmatches_res_1_np = unmatches_res_1_np.reshape(1, -1)
else:
unmatched_res_1_ids = unmatches_res_1['id'].to_list()
scores = unmatches_res_1['conf'].to_list()
online_im_1 = vis.plot_tracking(online_im_1,
unmatches_res_1_np,
unmatched_res_1_ids,
frame_id=frame,
fps=-1,
line_thickness_unmatched=4)
# ipdb.set_trace()
print(
f"{len(unmatches_res_1)} unmatches found in frame {frame}"
)
# Plot the unmatched in thicker colors
unmatches_res_2 = res_2_frame.iloc[u_res_2]
unmatches_res_2_np = np.array(
unmatches_res_2[['left', 'top', 'width', 'height']])
if len(unmatches_res_2) > 0:
if len(unmatches_res_2.shape) == 1:
unmatched_res_2_ids = [unmatches_res_2['id']]
scores = [unmatches_res_2['conf']]
unmatches_res_2_np = unmatches_res_2_np.reshape(1, -1)
else:
unmatched_res_2_ids = unmatches_res_2['id'].to_list()
scores = unmatches_res_2['conf'].to_list()
online_im_2 = vis.plot_tracking(online_im_2,
unmatches_res_2_np,
unmatched_res_2_ids,
frame_id=frame,
fps=-1,
line_thickness_unmatched=4)
cv2.imwrite(osp.join(save_root_1, f"{frame:06d}.jpg"),
online_im_1)
cv2.imwrite(osp.join(save_root_2, f"{frame:06d}.jpg"),
online_im_2)
else:
if len(res_1_boxes_np) > 0 and len(res_2_boxes_np) == 0:
matches_res_1 = res_1_frame
matches_res_1_np = np.array(
matches_res_1[['left', 'top', 'width', 'height']])
if len(matches_res_1.shape) == 1:
online_ids = [matches_res_1['id']]
scores = [matches_res_1['conf']]
else:
online_ids = matches_res_1['id'].to_list()
scores = matches_res_1['conf'].to_list()
online_im_1 = vis.plot_tracking(img1,
matches_res_1_np,
online_ids,
frame_id=frame,
fps=-1,
line_thickness_unmatched=4)
cv2.imwrite(osp.join(save_root_1, f"{frame:06d}.jpg"),
online_im_1)
cv2.imwrite(osp.join(save_root_2, f"{frame:06d}.jpg"),
img2)
if len(res_1_boxes_np) == 0 and len(res_2_boxes_np) > 0:
matches_res_2 = res_2_frame
matches_res_2_np = np.array(
matches_res_2[['left', 'top', 'width', 'height']])
if len(matches_res_2.shape) == 1:
online_ids = [matches_res_2['id']]
scores = [matches_res_2['conf']]
else:
online_ids = matches_res_2['id'].to_list()
scores = matches_res_2['conf'].to_list()
online_im_2 = vis.plot_tracking(img2,
matches_res_2_np,
online_ids,
frame_id=frame,
fps=-1,
line_thickness_unmatched=4)
cv2.imwrite(osp.join(save_root_1, f"{frame:06d}.jpg"),
img1)
cv2.imwrite(osp.join(save_root_2, f"{frame:06d}.jpg"),
online_im_2)
if len(res_1_boxes_np) == 0 and len(res_1_boxes_np) == 0:
cv2.imwrite(osp.join(save_root_1, f"{frame:06d}.jpg"),
img1)
cv2.imwrite(osp.join(save_root_2, f"{frame:06d}.jpg"),
img2)
cmd_str = 'ffmpeg -framerate 8 -y -f image2 -i {}/%06d.jpg -vcodec libx264 -c:v copy {}'.format(
save_root_1, osp.join(save_root_1, f'GNN_{seq}.avi'))
os.system(cmd_str)
cmd_str = 'ffmpeg -framerate 8 -y -f image2 -i {}/%06d.jpg -vcodec libx264 -c:v copy {}'.format(
save_root_2, osp.join(save_root_2, f'noGNN_{seq}.avi'))
os.system(cmd_str)
