def detect_chessboard(path, out, pattern, gridSize):
create_chessboard(path, pattern, gridSize)
dataset = ImageFolder(path, annot='chessboard')
dataset.isTmp = False
for i in tqdm(range(len(dataset))):
imgname, annotname = dataset[i]
# detect the 2d chessboard
img = cv2.imread(imgname)
annots = read_json(annotname)
show = findChessboardCorners(img, annots, pattern)
save_json(annotname, annots)
if show is None:
continue
outname = join(out, imgname.replace(path + '/images/', ''))
os.makedirs(os.path.dirname(outname), exist_ok=True)
cv2.imwrite(outname, show)
def detect_chessboard_sequence(path, out, pattern, gridSize, args):
create_chessboard(path, pattern, gridSize, ext=args.ext)
subs = sorted(os.listdir(join(path, 'images')))
for sub in subs:
dataset = ImageFolder(path, sub=sub, annot='chessboard', ext=args.ext)
dataset.isTmp = False
nFrames = len(dataset)
found = np.zeros(nFrames, dtype=np.bool)
visited = np.zeros(nFrames, dtype=np.bool)
proposals = []
init_step = args.max_step
min_step = args.min_step
for nf in range(0, nFrames, init_step):
if nf + init_step < len(dataset):
proposals.append([nf, nf + init_step])
while len(proposals) > 0:
left, right = proposals.pop(0)
print('Check [{}, {}]'.format(left, right))
for nf in [left, right]:
if not visited[nf]:
visited[nf] = True
imgname, annotname = dataset[nf]
# detect the 2d chessboard
img = cv2.imread(imgname)
annots = read_json(annotname)
show = findChessboardCorners(img, annots, pattern)
save_json(annotname, annots)
if show is None:
if args.debug:
print('Cannot find {}'.format(imgname))
found[nf] = False
continue
found[nf] = True
outname = join(out, imgname.replace(path + '/images/', ''))
os.makedirs(os.path.dirname(outname), exist_ok=True)
cv2.imwrite(outname, show)
if not found[left] and not found[right]:
continue
mid = (left + right) // 2
if mid == left or mid == right:
continue
if mid - left > min_step:
proposals.append((left, mid))
if right - mid > min_step:
proposals.append((mid, right))
def annot_example(path):
# define datasets
dataset = ImageFolder(path)
# define visualize
vis_funcs = [vis_point, vis_line]
# construct annotations
annotator = AnnotBase(dataset=dataset, key_funcs={}, vis_funcs=vis_funcs)
while annotator.isOpen:
annotator.run()
def detect_chessboard(path, out, pattern, gridSize, args):
create_chessboard(path, pattern, gridSize, ext=args.ext)
dataset = ImageFolder(path, annot='chessboard', ext=args.ext)
dataset.isTmp = False
if args.silent:
trange = range(len(dataset))
else:
trange = tqdm(range(len(dataset)))
for i in trange:
imgname, annotname = dataset[i]
# detect the 2d chessboard
img = cv2.imread(imgname)
annots = read_json(annotname)
show = findChessboardCorners(img, annots, pattern)
save_json(annotname, annots)
if show is None:
if args.debug:
print('Cannot find {}'.format(imgname))
continue
outname = join(out, imgname.replace(path + '/images/', ''))
os.makedirs(os.path.dirname(outname), exist_ok=True)
cv2.imwrite(outname, show)
def annot_example(path, sub, image, annot, step, args):
# define datasets
dataset = ImageFolder(path, sub=sub, image=image, annot=annot)
key_funcs = {
'v': set_unvisible,
'V': set_unvisible_according_previous,
'f': set_face_unvisible,
'c': check_track,
'm': mirror_keypoints2d,
'M': mirror_keypoints2d_leg,
}
if args.hrnet:
estimator = Estimator()
key_funcs['e'] = estimator.detect_with_bbox
key_funcs['r'] = estimator.detect_with_bbox90
key_funcs['t'] = estimator.detect_with_bbox180
key_funcs['y'] = estimator.detect_with_bbox270
key_funcs['g'] = estimator.detect_with_previous_slow
key_funcs['j'] = estimator.detect_with_previous_mid
# callback of bounding box
callbacks = [
callback_select_bbox_corner, callback_select_bbox_center,
callback_select_joints
]
# callback of keypoints
# define visualize
vis_funcs = [plot_skeleton_factory('body25'), vis_bbox, vis_active_bbox]
if args.hand:
vis_funcs += [
plot_bbox_factory('bbox_handl2d'),
plot_bbox_factory('bbox_handr2d'),
plot_bbox_factory('bbox_face2d')
]
vis_funcs += [
plot_skeleton_factory('handl'),
plot_skeleton_factory('handr'),
plot_skeleton_factory('face')
]
vis_funcs += [resize_to_screen, plot_text, capture_screen]
# construct annotations
annotator = AnnotBase(dataset=dataset,
key_funcs=key_funcs,
vis_funcs=vis_funcs,
callbacks=callbacks,
name=sub,
step=step)
while annotator.isOpen:
annotator.run()
def annot_example(path, subs, annot, step):
for sub in subs:
# define datasets
dataset = ImageFolder(path, sub=sub, annot=annot)
key_funcs = {'t': auto_pose_track}
callbacks = [callback_select_bbox_corner, callback_select_bbox_center]
# define visualize
vis_funcs = [vis_line, plot_bbox_body, vis_active_bbox]
# construct annotations
annotator = AnnotBase(dataset=dataset,
key_funcs=key_funcs,
vis_funcs=vis_funcs,
callbacks=callbacks,
name=sub,
step=step)
while annotator.isOpen:
annotator.run()
def annot_example(path, args):
# define datasets
calib = Matcher(path, mode=args.mode, args=args)
dataset = ImageFolder(path, annot=args.annot)
# define visualize
vis_funcs = [vis_point, vis_line, calib.vis, resize_to_screen, plot_text]
key_funcs = {
' ': calib.add,
'z': calib.add_conf,
'p': calib.add_point_by_2lines,
'c': calib.clear_point,
'C': calib.clear,
}
# construct annotations
annotator = AnnotBase(dataset=dataset,
key_funcs=key_funcs,
vis_funcs=vis_funcs)
while annotator.isOpen:
annotator.run()
def annot_example(path, annot, sub=None, step=100):
# define datasets
dataset = ImageFolder(path, sub=sub, annot=annot)
key_funcs = {
'X': get_record_vanish_lines(0),
'Y': get_record_vanish_lines(1),
'Z': get_record_vanish_lines(2),
'k': get_calc_intrinsic('xy'),
'K': get_calc_intrinsic('yz'),
'b': vanish_point_from_body,
'C': clear_vanish_points,
'B': clear_body_points,
'c': copy_edges_from_cache,
'v': copy_edges
}
# define visualize
vis_funcs = [vis_line, plot_skeleton, vis_vanish_lines, plot_text]
# construct annotations
annotator = AnnotBase(dataset=dataset,
key_funcs=key_funcs,
vis_funcs=vis_funcs,
step=step)
annots = annotator.param['annots']
print(sub)
annotator.run('X')
annotator.run('Y')
annotator.run('Z')
annotator.run('k')
if 'K' in annots.keys() and False:
print('\n'.join([
' '.join(['{:7.2f}'.format(i) for i in row]) for row in annots['K']
]))
return 0
else:
print('K is not caculated')
while annotator.isOpen:
annotator.run()
for key in ['vanish_line', 'vanish_point']:
edges_cache[key] = annotator.param['annots'][key]
def annot_example(path, annot, sub=None, step=100):
# define datasets
dataset = ImageFolder(path, sub=sub, annot=annot)
key_funcs = {
'X': get_record_vanish_lines(0),
'Y': get_record_vanish_lines(1),
'Z': get_record_vanish_lines(2),
'k': get_calc_intrinsic('xy'),
'K': get_calc_intrinsic('yz'),
'b': vanish_point_from_body,
'C': clear_vanish_points,
'B': clear_body_points,
'c': copy_edges,
}
# define visualize
vis_funcs = [vis_line, plot_skeleton_simple, vis_vanish_lines]
# construct annotations
annotator = AnnotBase(dataset=dataset,
key_funcs=key_funcs,
vis_funcs=vis_funcs,
step=step)
while annotator.isOpen:
annotator.run()