From b56711f7a5c1281a9b396dad40f7980b4ec930ec Mon Sep 17 00:00:00 2001 From: silencht Date: Thu, 12 Dec 2024 20:00:49 +0800 Subject: [PATCH] [update] 1. Data recording using multithreading (.json not yet implemented) 2. Optimize rerun (not fully implemented yet). --- .gitignore | 3 +- teleop/open_television/tv_wrapper.py | 4 +- teleop/robot_control/robot_arm.py | 2 +- teleop/robot_control/robot_hand_unitree.py | 21 ++- teleop/teleop_hand_and_arm.py | 11 +- teleop/utils/episode_writer.py | 113 ++++++++++----- teleop/utils/rerun_visualizer.py | 155 +++++++++++---------- 7 files changed, 186 insertions(+), 123 deletions(-) diff --git a/.gitignore b/.gitignore index de07d14..47d647e 100644 --- a/.gitignore +++ b/.gitignore @@ -19,5 +19,4 @@ __MACOSX/ !real_right_hand.jpg !wrist_and_ring_mount.png teleop/data/ -teleop/utils/episode_0* -teleop/utils/data/episode_0* \ No newline at end of file +episode_0* \ No newline at end of file diff --git a/teleop/open_television/tv_wrapper.py b/teleop/open_television/tv_wrapper.py index 1bcbd85..9f0b733 100644 --- a/teleop/open_television/tv_wrapper.py +++ b/teleop/open_television/tv_wrapper.py @@ -139,8 +139,8 @@ def get_data(self): head_rmat = head_mat[:3, :3] # The origin of the coordinate for IK Solve is the WAIST joint motor. You can use teleop/robot_control/robot_arm_ik.py Unit_Test to check it. # The origin of the coordinate of unitree_left_wrist is HEAD. So it is necessary to translate the origin of unitree_left_wrist from HEAD to WAIST. - unitree_left_wrist[0, 3] +=0.20 - unitree_right_wrist[0,3] +=0.20 + unitree_left_wrist[0, 3] +=0.15 + unitree_right_wrist[0,3] +=0.15 unitree_left_wrist[2, 3] +=0.45 unitree_right_wrist[2,3] +=0.45 diff --git a/teleop/robot_control/robot_arm.py b/teleop/robot_control/robot_arm.py index 47204d4..e72da77 100644 --- a/teleop/robot_control/robot_arm.py +++ b/teleop/robot_control/robot_arm.py @@ -41,7 +41,7 @@ def __init__(self): self.q_target = np.zeros(14) self.tauff_target = np.zeros(14) - self.kp_high = 100.0 + self.kp_high = 300.0 self.kd_high = 3.0 self.kp_low = 80.0 self.kd_low = 3.0 diff --git a/teleop/robot_control/robot_hand_unitree.py b/teleop/robot_control/robot_hand_unitree.py index e4489f7..9968db7 100644 --- a/teleop/robot_control/robot_hand_unitree.py +++ b/teleop/robot_control/robot_hand_unitree.py @@ -18,6 +18,7 @@ parent2_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) sys.path.append(parent2_dir) from teleop.robot_control.hand_retargeting import HandRetargeting, HandType +from teleop.utils.weighted_moving_filter import WeightedMovingFilter unitree_tip_indices = [4, 9, 14] # [thumb, index, middle] in OpenXR @@ -228,7 +229,7 @@ class Dex3_1_Right_JointIndex(IntEnum): class Gripper_Controller: def __init__(self, left_hand_array, right_hand_array, dual_gripper_data_lock = None, dual_gripper_state_out = None, dual_gripper_action_out = None, - fps = 250.0, Unit_Test = False): + filter = True, fps = 200.0, Unit_Test = False): """ [note] A *_array type parameter requires using a multiprocessing Array, because it needs to be passed to the internal child process @@ -251,6 +252,10 @@ def __init__(self, left_hand_array, right_hand_array, dual_gripper_data_lock = N self.fps = fps self.Unit_Test = Unit_Test + if filter: + self.smooth_filter = WeightedMovingFilter(np.array([0.5, 0.3, 0.2]), Gripper_Num_Motors) + else: + self.smooth_filter = None if self.Unit_Test: ChannelFactoryInitialize(0) @@ -303,8 +308,8 @@ def control_thread(self, left_hand_array, right_hand_array, dual_gripper_state_i self.running = True DELTA_GRIPPER_CMD = 0.18 # The motor rotates 5.4 radians, the clamping jaw slide open 9 cm, so 0.6 rad <==> 1 cm, 0.18 rad <==> 3 mm - THUMB_INDEX_DISTANCE_MIN = 0.030 # Assuming a minimum Euclidean distance is 3 cm between thumb and index. - THUMB_INDEX_DISTANCE_MAX = 0.120 # Assuming a maximum Euclidean distance is 12 cm between thumb and index. + THUMB_INDEX_DISTANCE_MIN = 0.05 # Assuming a minimum Euclidean distance is 5 cm between thumb and index. + THUMB_INDEX_DISTANCE_MAX = 0.07 # Assuming a maximum Euclidean distance is 9 cm between thumb and index. LEFT_MAPPED_MIN = 0.0 # The minimum initial motor position when the gripper closes at startup. RIGHT_MAPPED_MIN = 0.0 # The minimum initial motor position when the gripper closes at startup. # The maximum initial motor position when the gripper closes before calibration (with the rail stroke calculated as 0.6 cm/rad * 9 rad = 5.4 cm). @@ -315,7 +320,7 @@ def control_thread(self, left_hand_array, right_hand_array, dual_gripper_state_i dq = 0.0 tau = 0.0 - kp = 5.0 + kp = 5.00 kd = 0.05 # initialize gripper cmd msg self.gripper_msg = MotorCmds_() @@ -335,11 +340,11 @@ def control_thread(self, left_hand_array, right_hand_array, dual_gripper_state_i if not np.all(left_hand_mat == 0.0): # if hand data has been initialized. left_euclidean_distance = np.linalg.norm(left_hand_mat[unitree_gripper_indices[1]] - left_hand_mat[unitree_gripper_indices[0]]) - right_euclidean_distance = np.linalg.norm(right_hand_mat[unitree_gripper_indices[1]] - left_hand_mat[unitree_gripper_indices[0]]) + right_euclidean_distance = np.linalg.norm(right_hand_mat[unitree_gripper_indices[1]] - right_hand_mat[unitree_gripper_indices[0]]) # Linear mapping from [0, THUMB_INDEX_DISTANCE_MAX] to gripper action range left_target_action = np.interp(left_euclidean_distance, [THUMB_INDEX_DISTANCE_MIN, THUMB_INDEX_DISTANCE_MAX], [LEFT_MAPPED_MIN, LEFT_MAPPED_MAX]) right_target_action = np.interp(right_euclidean_distance, [THUMB_INDEX_DISTANCE_MIN, THUMB_INDEX_DISTANCE_MAX], [RIGHT_MAPPED_MIN, RIGHT_MAPPED_MAX]) - # else: # TEST WITHOUT APPLE VISION PRO + # else: # TEST WITHOUT XR DEVICE # current_time = time.time() # period = 2.5 # import math @@ -357,6 +362,10 @@ def control_thread(self, left_hand_array, right_hand_array, dual_gripper_state_i dual_gripper_action = np.array([right_actual_action, left_actual_action]) + if self.smooth_filter: + self.smooth_filter.add_data(dual_gripper_action) + dual_gripper_action = self.smooth_filter.filtered_data + if dual_gripper_state_out and dual_gripper_action_out: with dual_hand_data_lock: dual_gripper_state_out[:] = dual_gripper_state - np.array([RIGHT_MAPPED_MIN, LEFT_MAPPED_MIN]) diff --git a/teleop/teleop_hand_and_arm.py b/teleop/teleop_hand_and_arm.py index 0e245b3..7f89057 100644 --- a/teleop/teleop_hand_and_arm.py +++ b/teleop/teleop_hand_and_arm.py @@ -97,7 +97,7 @@ gripper_ctrl = Gripper_Controller(left_hand_array, right_hand_array, dual_gripper_data_lock, dual_gripper_state_array, dual_gripper_action_array) if args.record: - recorder = EpisodeWriter(task_dir = args.task_dir, frequency = args.frequency, log = True) + recorder = EpisodeWriter(task_dir = args.task_dir, frequency = args.frequency, rerun_log = True) try: user_input = input("Please enter the start signal (enter 'r' to start the subsequent program):\n") @@ -156,10 +156,10 @@ right_hand_action = dual_hand_action_array[-7:] else: with dual_gripper_data_lock: - left_hand_state = dual_gripper_state_array[1] - right_hand_state = dual_gripper_state_array[0] - left_hand_action = dual_gripper_action_array[1] - right_hand_action = dual_gripper_action_array[0] + left_hand_state = [dual_gripper_state_array[1]] + right_hand_state = [dual_gripper_state_array[0]] + left_hand_action = [dual_gripper_action_array[1]] + right_hand_action = [dual_gripper_action_array[0]] # head image current_tv_image = tv_img_array.copy() # wrist image @@ -247,5 +247,6 @@ if WRIST: wrist_img_shm.unlink() wrist_img_shm.close() + recorder.close() print("Finally, exiting program...") exit(0) \ No newline at end of file diff --git a/teleop/utils/episode_writer.py b/teleop/utils/episode_writer.py index 80216d5..d99130d 100755 --- a/teleop/utils/episode_writer.py +++ b/teleop/utils/episode_writer.py @@ -5,10 +5,11 @@ import numpy as np import time from .rerun_visualizer import RerunLogger - +from queue import Queue, Empty +from threading import Thread class EpisodeWriter(): - def __init__(self, task_dir, frequency=30, image_size=[640, 480], log = False): + def __init__(self, task_dir, frequency=30, image_size=[640, 480], rerun_log = True): """ image_size: [width, height] """ @@ -16,28 +17,40 @@ def __init__(self, task_dir, frequency=30, image_size=[640, 480], log = False): self.task_dir = task_dir self.frequency = frequency self.image_size = image_size + + self.rerun_log = rerun_log + if self.rerun_log: + print("==> RerunLogger initializing...\n") + self.rerun_logger = RerunLogger(prefix="online/", IdxRangeBoundary = 60, memory_limit = "300MB") + print("==> RerunLogger initializing ok.\n") self.data = {} self.episode_data = [] self.item_id = -1 self.episode_id = -1 - self.log = log if os.path.exists(self.task_dir): episode_dirs = [episode_dir for episode_dir in os.listdir(self.task_dir) if 'episode_' in episode_dir] episode_last = sorted(episode_dirs)[-1] if len(episode_dirs) > 0 else None self.episode_id = 0 if episode_last is None else int(episode_last.split('_')[-1]) - print(f"==> task_dir directory already exist, now self.episode_id is：{self.episode_id}\n") + print(f"==> task_dir directory already exist, now self.episode_id is:{self.episode_id}\n") else: os.makedirs(self.task_dir) print(f"==> episode directory does not exist, now create one.\n") self.data_info() self.text_desc() + + # Initialize the queue and worker thread + self.item_data_queue = Queue(maxsize=100) + self.stop_worker = False + self.worker_thread = Thread(target=self.process_queue) + self.worker_thread.start() + print("==> EpisodeWriter initialized successfully.\n") def data_info(self, version='1.0.0', date=None, author=None): self.info = { "version": "1.0.0" if version is None else version, - "date": "" if date is None else datetime.date.today().strftime('%Y-%m-%d'), + "date": datetime.date.today().strftime('%Y-%m-%d') if date is None else date, "author": "unitree" if author is None else author, "image": {"width":self.image_size[0], "height":self.image_size[1], "fps":self.frequency}, "depth": {"width":self.image_size[0], "height":self.image_size[1], "fps":self.frequency}, @@ -85,63 +98,91 @@ def create_episode(self): os.makedirs(self.color_dir, exist_ok=True) os.makedirs(self.depth_dir, exist_ok=True) os.makedirs(self.audio_dir, exist_ok=True) - if self.log: - self.online_logger = RerunLogger(prefix="online/", IdxRangeBoundary = 60) + if self.rerun_log: + self.online_logger = RerunLogger(prefix="online/", IdxRangeBoundary = 60, memory_limit="300MB") def add_item(self, colors, depths=None, states=None, actions=None, tactiles=None, audios=None): + # Increment the item ID self.item_id += 1 + # Create the item data dictionary item_data = { 'idx': self.item_id, - 'colors': {"color_0": None}, - 'depths': {"depth_0": None}, - 'states': {'left_arm':{}, 'right_arm':{}, 'left_hand':{}, 'right_hand':{}, 'body': {}}, - 'actions': {'left_arm':{}, 'right_arm':{}, 'left_hand':{}, 'right_hand':{}, 'body': {}}, - 'tactiles': {'left_hand':[], 'right_hand':[]}, - 'audios': { "mic0": None}, + 'colors': colors, + 'depths': depths, + 'states': states, + 'actions': actions, + 'tactiles': tactiles, + 'audios': audios, } + # Enqueue the item data + self.item_data_queue.put(item_data) + + def process_queue(self): + while not self.stop_worker or not self.item_data_queue.empty(): + try: + item_data = self.item_data_queue.get(timeout=1) + try: + self._process_item_data(item_data) + except Exception as e: + print(f"Error processing item_data (idx={item_data['idx']}): {e}") + self.item_data_queue.task_done() + except Empty: + continue - # save images - if colors is not None: - for idx, (_, color) in enumerate(colors.items()): - color_key = f'color_{idx}' - color_name = f'{str(self.item_id).zfill(6)}_{color_key}.jpg' - cv2.imwrite(os.path.join(self.color_dir, color_name), color) + def _process_item_data(self, item_data): + idx = item_data['idx'] + colors = item_data.get('colors', {}) + depths = item_data.get('depths', {}) + audios = item_data.get('audios', {}) + + # Save images + if colors: + for idx_color, (color_key, color) in enumerate(colors.items()): + color_name = f'{str(idx).zfill(6)}_{color_key}.jpg' + if not cv2.imwrite(os.path.join(self.color_dir, color_name), color): + print(f"Failed to save color image.") item_data['colors'][color_key] = os.path.join('colors', color_name) - # save depths - if depths is not None: - for idx, (_, depth) in enumerate(depths.items()): - depth_key = f'depth_{idx}' - depth_name = f'{str(self.item_id).zfill(6)}_{depth_key}.png' - cv2.imwrite(os.path.join(self.depth_dir, depth_name), depth) + # Save depths + if depths: + for idx_depth, (depth_key, depth) in enumerate(depths.items()): + depth_name = f'{str(idx).zfill(6)}_{depth_key}.jpg' + if not cv2.imwrite(os.path.join(self.depth_dir, depth_name), depth): + print(f"Failed to save depth image.") item_data['depths'][depth_key] = os.path.join('depths', depth_name) - # save audios - if audios is not None: + # Save audios + if audios: for mic, audio in audios.items(): - audio_name = f'audio_{str(self.item_id).zfill(6)}_{mic}.npy' + audio_name = f'audio_{str(idx).zfill(6)}_{mic}.npy' np.save(os.path.join(self.audio_dir, audio_name), audio.astype(np.int16)) item_data['audios'][mic] = os.path.join('audios', audio_name) - item_data['states'] = states - item_data['actions'] = actions - item_data['tactiles'] = tactiles - + # Update episode data self.episode_data.append(item_data) - if self.log: + # Log data if necessary + if self.rerun_log: curent_record_time = time.time() print(f"==> episode_id:{self.episode_id} item_id:{self.item_id} current_time:{curent_record_time}") - self.online_logger.log_item_data(item_data) - + self.rerun_logger.log_item_data(item_data) def save_episode(self): """ with open("./hmm.json",'r',encoding='utf-8') as json_file: model=json.load(json_file) """ + # Wait for the queue to be processed + self.item_data_queue.join() + # save self.data['info'] = self.info self.data['text'] = self.text self.data['data'] = self.episode_data with open(self.json_path,'w',encoding='utf-8') as jsonf: - jsonf.write(json.dumps(self.data, indent=4, ensure_ascii=False)) \ No newline at end of file + jsonf.write(json.dumps(self.data, indent=4, ensure_ascii=False)) + + def close(self): + self.item_data_queue.join() + # Signal the worker thread to stop and join the thread + self.stop_worker = True + self.worker_thread.join() \ No newline at end of file diff --git a/teleop/utils/rerun_visualizer.py b/teleop/utils/rerun_visualizer.py index c7ac9a6..c11a10e 100644 --- a/teleop/utils/rerun_visualizer.py +++ b/teleop/utils/rerun_visualizer.py @@ -70,31 +70,28 @@ def _process_audio(self, item_data, data_type, episode_dir): return audio_data class RerunLogger: - def __init__(self, prefix = "", IdxRangeBoundary = 30, memory_limit = "200MB"): - rr.init(datetime.now().strftime("Runtime_%Y%m%d_%H%M%S")) - rr.spawn(memory_limit = memory_limit) - + def __init__(self, prefix = "", IdxRangeBoundary = 30, memory_limit = None): self.prefix = prefix self.IdxRangeBoundary = IdxRangeBoundary + rr.init(datetime.now().strftime("Runtime_%Y%m%d_%H%M%S")) + if memory_limit: + rr.spawn(memory_limit = memory_limit, hide_welcome_screen = True) + else: + rr.spawn(hide_welcome_screen = True) + # Set up blueprint for live visualization if self.IdxRangeBoundary: self.setup_blueprint() def setup_blueprint(self): + views = [] + data_plot_paths = [ f"{self.prefix}left_arm", f"{self.prefix}right_arm", f"{self.prefix}left_hand", f"{self.prefix}right_hand" ] - image_plot_paths = [ - f"{self.prefix}colors/color_0", - f"{self.prefix}colors/color_1", - f"{self.prefix}colors/color_2", - f"{self.prefix}colors/color_3" - ] - - views = [] for plot_path in data_plot_paths: view = rrb.TimeSeriesView( origin = plot_path, @@ -109,24 +106,32 @@ def setup_blueprint(self): ) views.append(view) - for plot_path in image_plot_paths: - view = rrb.Spatial2DView( - origin = plot_path, - time_ranges=[ - rrb.VisibleTimeRange( - "idx", - start = rrb.TimeRangeBoundary.cursor_relative(seq = -self.IdxRangeBoundary), - end = rrb.TimeRangeBoundary.cursor_relative(), - ) - ], - ) - views.append(view) + # image_plot_paths = [ + # f"{self.prefix}colors/color_0", + # f"{self.prefix}colors/color_1", + # f"{self.prefix}colors/color_2", + # f"{self.prefix}colors/color_3" + # ] + # for plot_path in image_plot_paths: + # view = rrb.Spatial2DView( + # origin = plot_path, + # time_ranges=[ + # rrb.VisibleTimeRange( + # "idx", + # start = rrb.TimeRangeBoundary.cursor_relative(seq = -self.IdxRangeBoundary), + # end = rrb.TimeRangeBoundary.cursor_relative(), + # ) + # ], + # ) + # views.append(view) grid = rrb.Grid(contents = views, grid_columns=2, column_shares=[1, 1], - row_shares=[1, 1, 0.5], + row_shares=[1, 1], ) + views.append(rr.blueprint.SelectionPanel(state=rrb.PanelState.Collapsed)) + views.append(rr.blueprint.TimePanel(state=rrb.PanelState.Collapsed)) rr.send_blueprint(grid) @@ -149,30 +154,30 @@ def log_item_data(self, item_data: dict): for idx, val in enumerate(values): rr.log(f"{self.prefix}{part}/actions/qpos/{idx}", rr.Scalar(val)) - # Log colors (images) - colors = item_data.get('colors', {}) or {} - for color_key, color_val in colors.items(): - if color_val is not None: - rr.log(f"{self.prefix}colors/{color_key}", rr.Image(color_val)) - - # Log depths (images) - depths = item_data.get('depths', {}) or {} - for depth_key, depth_val in depths.items(): - if depth_val is not None: - # rr.log(f"{self.prefix}depths/{depth_key}", rr.Image(depth_val)) - pass # Handle depth if needed - - # Log tactile if needed - tactiles = item_data.get('tactiles', {}) or {} - for hand, tactile_vals in tactiles.items(): - if tactile_vals is not None: - pass # Handle tactile if needed - - # Log audios if needed - audios = item_data.get('audios', {}) or {} - for audio_key, audio_val in audios.items(): - if audio_val is not None: - pass # Handle audios if needed + # # Log colors (images) + # colors = item_data.get('colors', {}) or {} + # for color_key, color_val in colors.items(): + # if color_val is not None: + # rr.log(f"{self.prefix}colors/{color_key}", rr.Image(color_val)) + + # # Log depths (images) + # depths = item_data.get('depths', {}) or {} + # for depth_key, depth_val in depths.items(): + # if depth_val is not None: + # # rr.log(f"{self.prefix}depths/{depth_key}", rr.Image(depth_val)) + # pass # Handle depth if needed + + # # Log tactile if needed + # tactiles = item_data.get('tactiles', {}) or {} + # for hand, tactile_vals in tactiles.items(): + # if tactile_vals is not None: + # pass # Handle tactile if needed + + # # Log audios if needed + # audios = item_data.get('audios', {}) or {} + # for audio_key, audio_val in audios.items(): + # if audio_val is not None: + # pass # Handle audios if needed def log_episode_data(self, episode_data: list): for item_data in episode_data: @@ -183,49 +188,57 @@ def log_episode_data(self, episode_data: list): import gdown import zipfile import os - url = "https://drive.google.com/file/d/1f5UuFl1z_gaByg_7jDRj1_NxfJZh2evD/view?usp=sharing" zip_file = "rerun_testdata.zip" - if not os.path.exists("episode_0006"): + zip_file_download_url = "https://drive.google.com/file/d/1f5UuFl1z_gaByg_7jDRj1_NxfJZh2evD/view?usp=sharing" + unzip_file_output_dir = "./testdata" + if not os.path.exists(os.path.join(unzip_file_output_dir, "episode_0006")): if not os.path.exists(zip_file): - file_id = url.split('/')[5] + file_id = zip_file_download_url.split('/')[5] gdown.download(id=file_id, output=zip_file, quiet=False) print("download ok.") + if not os.path.exists(unzip_file_output_dir): + os.makedirs(unzip_file_output_dir) with zipfile.ZipFile(zip_file, 'r') as zip_ref: - zip_ref.extractall(".") + zip_ref.extractall(unzip_file_output_dir) print("uncompress ok.") os.remove(zip_file) print("clean file ok.") else: print("rerun_testdata exits.") - episode_reader = RerunEpisodeReader(task_dir=".") - episode_data6 = episode_reader.return_episode_data(6) - episode_data8 = episode_reader.return_episode_data(8) - # Example 1: Offline Visualization - user_input = input("Please enter the start signal (enter 'off' to start the subsequent program):\n") + episode_reader = RerunEpisodeReader(task_dir = unzip_file_output_dir) + # TEST EXAMPLE 1 : OFFLINE DATA TEST + user_input = input("Please enter the start signal (enter 'off' or 'on' to start the subsequent program):\n") if user_input.lower() == 'off': + episode_data6 = episode_reader.return_episode_data(6) print("Starting offline visualization...") offline_logger = RerunLogger(prefix="offline/") offline_logger.log_episode_data(episode_data6) print("Offline visualization completed.") - # Example 2: Online Visualization with Fixed Time Window - user_input = input("Please enter the start signal (enter 'on' to start the subsequent program):\n") + # TEST EXAMPLE 2 : ONLINE DATA TEST, SLIDE WINDOW SIZE IS 60, MEMORY LIMIT IS 50MB if user_input.lower() == 'on': + episode_data8 = episode_reader.return_episode_data(8) print("Starting online visualization with fixed idx size...") - online_logger = RerunLogger(prefix="online/", IdxRangeBoundary = 60) - for item_data in episode_data6: + online_logger = RerunLogger(prefix="online/", IdxRangeBoundary = 60, memory_limit='50MB') + for item_data in episode_data8: online_logger.log_item_data(item_data) time.sleep(0.033) # 30hz print("Online visualization completed.") - # Example 3: Online Visualization with Fixed Time Window - user_input = input("Please enter the start signal (enter 'on' to start the subsequent program):\n") - if user_input.lower() == 'on': - print("Starting online visualization with fixed idx size...") - online_logger = RerunLogger(prefix="online/", IdxRangeBoundary = 60) - for item_data in episode_data8: - online_logger.log_item_data(item_data) - time.sleep(0.033) # 30hz - print("Online visualization completed.") \ No newline at end of file + + # # TEST DATA OF data_dir + # data_dir = "./data" + # episode_data_number = 10 + # episode_reader2 = RerunEpisodeReader(task_dir = data_dir) + # user_input = input("Please enter the start signal (enter 'on' to start the subsequent program):\n") + # episode_data8 = episode_reader2.return_episode_data(episode_data_number) + # if user_input.lower() == 'on': + # # Example 2: Offline Visualization with Fixed Time Window + # print("Starting offline visualization with fixed idx size...") + # online_logger = RerunLogger(prefix="offline/", IdxRangeBoundary = 60) + # for item_data in episode_data8: + # online_logger.log_item_data(item_data) + # time.sleep(0.033) # 30hz + # print("Offline visualization completed.") \ No newline at end of file