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!")