for home, dirs, files in os.walk(video_root):
for filename in files:
video_list.append(os.path.join(home, filename))
playback_handle = k4a.k4a_playback_t()
for v_i, video_dir in enumerate(video_list):
print_toolbar(v_i * 1.0 / len(video_list),
'({:>5}/{:<5}) Processing data: '.format(
v_i + 1, len(video_list)))
video_name = video_dir.split('/')[-1].split('.')[0]
label_name = video_dir.split('/')[-1].split('_')[0]
# open file
VERIFY(k4a.k4a_playback_open(ctypes.c_char_p(bytes(video_dir, encoding='utf8')), ctypes.byref(playback_handle)), "Cannot open recording {}!".format(video_dir))
sensor_calibration = k4a.k4a_calibration_t()
VERIFY(k4a.k4a_playback_get_calibration(playback_handle, ctypes.byref(sensor_calibration)), "Get depth camera calibration failed!")
tracker = k4a.k4abt_tracker_t()
tracker_config = k4a.K4ABT_TRACKER_CONFIG_DEFAULT
VERIFY(k4a.k4abt_tracker_create(ctypes.byref(sensor_calibration), tracker_config, ctypes.byref(tracker)), "Body tracker initialization failed!")
js_dict = {'data':[], 'label': label_name,'label_index':label_index_map[label_name]}
if video_name not in js_label_dict.keys():
js_label_dict[video_name] = {"has_skeleton": True, "label": label_name, "label_index": label_index_map[label_name]}
frame_count = 0
while frame_count < 300:
# VERIFY(k4a.k4a_device_get_calibration(device, device_config.depth_mode, k4a.K4A_COLOR_RESOLUTION_OFF, ctypes.byref(sensor_calibration)), "Get depth camera calibration failed!")
# print(sensor_calibration.depth_camera_calibration.intrinsics.parameters.param.cx)
# # import pdb; pdb.set_trace()
# k4a.k4a_device_stop_cameras(device)
# k4a.k4a_device_close(device)
device_config = k4a.K4A_DEVICE_CONFIG_INIT_DISABLE_ALL
device_config.depth_mode = k4a.K4A_DEPTH_MODE_NFOV_UNBINNED
# open file
playback_handle = k4a.k4a_playback_t()
mkv_path = 'G:/dataset/installing_1.mkv'
VERIFY(
k4a.k4a_playback_open(
ctypes.c_char_p(bytes(mkv_path, encoding='utf8')),
ctypes.byref(playback_handle)),
"Cannot open recording {}!".format(mkv_path))
sensor_calibration = k4a.k4a_calibration_t()
VERIFY(
k4a.k4a_playback_get_calibration(playback_handle,
ctypes.byref(sensor_calibration)),
"Get depth camera calibration failed!")
dep_in_cx = sensor_calibration.depth_camera_calibration.intrinsics.parameters.param.cx
dep_in_cy = sensor_calibration.depth_camera_calibration.intrinsics.parameters.param.cy
dep_in_fx = sensor_calibration.depth_camera_calibration.intrinsics.parameters.param.fx
dep_in_fy = sensor_calibration.depth_camera_calibration.intrinsics.parameters.param.fy
dep_in_mat = np.mat([[dep_in_fx, 0, dep_in_cx], [0, dep_in_fy, dep_in_cy],
[0, 0, 1]])
video_list.append(os.path.join(home, filename))
playback_handle = k4a.k4a_playback_t()
for v_i, video_dir in enumerate(video_list):
print_toolbar(
v_i * 1.0 / len(video_list),
'({:>5}/{:<5}) Processing data: '.format(v_i + 1, len(video_list)))
video_name = video_dir.split('/')[-1].split('.')[0]
label_name = video_dir.split('/')[-1].split('_')[0]
# open file
VERIFY(
k4a.k4a_playback_open(
ctypes.c_char_p(bytes(video_dir, encoding='utf8')),
ctypes.byref(playback_handle)),
"Cannot open recording {}!".format(video_dir))
sensor_calibration = k4a.k4a_calibration_t()
VERIFY(
k4a.k4a_playback_get_calibration(playback_handle,
ctypes.byref(sensor_calibration)),
"Get depth camera calibration failed!")
tracker = k4a.k4abt_tracker_t()
tracker_config = k4a.K4ABT_TRACKER_CONFIG_DEFAULT
VERIFY(
k4a.k4abt_tracker_create(ctypes.byref(sensor_calibration),
tracker_config, ctypes.byref(tracker)),
"Body tracker initialization failed!")