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chore(examples): homogenize style across example files (#1955)
* chore(examples): homogenize style across example files * chore(examples): homogenize style across example files eval + replay * chore(examples): homogenize headers
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@@ -1,5 +1,22 @@
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# !/usr/bin/env python
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# Copyright 2025 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from lerobot.datasets.lerobot_dataset import LeRobotDataset
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from lerobot.datasets.utils import hw_to_dataset_features
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from lerobot.processor import make_default_processors
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from lerobot.record import record_loop
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from lerobot.robots.lekiwi.config_lekiwi import LeKiwiClientConfig
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from lerobot.robots.lekiwi.lekiwi_client import LeKiwiClient
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@@ -14,16 +31,21 @@ FPS = 30
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EPISODE_TIME_SEC = 30
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RESET_TIME_SEC = 10
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TASK_DESCRIPTION = "My task description"
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HF_REPO_ID = "<hf_username>/<dataset_repo_id>"
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# Create the robot and teleoperator configurations
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robot_config = LeKiwiClientConfig(remote_ip="172.18.134.136", id="lekiwi")
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leader_arm_config = SO100LeaderConfig(port="/dev/tty.usbmodem585A0077581", id="my_awesome_leader_arm")
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keyboard_config = KeyboardTeleopConfig()
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# Initialize the robot and teleoperator
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robot = LeKiwiClient(robot_config)
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leader_arm = SO100Leader(leader_arm_config)
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keyboard = KeyboardTeleop(keyboard_config)
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# TODO(Steven): Update this example to use pipelines
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teleop_action_processor, robot_action_processor, robot_observation_processor = make_default_processors()
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# Configure the dataset features
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action_features = hw_to_dataset_features(robot.action_features, "action")
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obs_features = hw_to_dataset_features(robot.observation_features, "observation")
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@@ -31,7 +53,7 @@ dataset_features = {**action_features, **obs_features}
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# Create the dataset
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dataset = LeRobotDataset.create(
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repo_id="<hf_username>/<dataset_repo_id>",
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repo_id=HF_REPO_ID,
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fps=FPS,
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features=dataset_features,
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robot_type=robot.name,
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@@ -39,23 +61,25 @@ dataset = LeRobotDataset.create(
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image_writer_threads=4,
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)
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# Connect the robot and teleoperator
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# To connect you already should have this script running on LeKiwi: `python -m lerobot.robots.lekiwi.lekiwi_host --robot.id=my_awesome_kiwi`
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robot.connect()
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leader_arm.connect()
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keyboard.connect()
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# Initialize the keyboard listener and rerun visualization
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listener, events = init_keyboard_listener()
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_init_rerun(session_name="lekiwi_record")
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listener, events = init_keyboard_listener()
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if not robot.is_connected or not leader_arm.is_connected or not keyboard.is_connected:
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raise ValueError("Robot, leader arm of keyboard is not connected!")
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raise ValueError("Robot or teleop is not connected!")
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print("Starting record loop...")
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recorded_episodes = 0
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while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
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log_say(f"Recording episode {recorded_episodes}")
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# Run the record loop
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# Main record loop
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record_loop(
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robot=robot,
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events=events,
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@@ -65,9 +89,12 @@ while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
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control_time_s=EPISODE_TIME_SEC,
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single_task=TASK_DESCRIPTION,
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display_data=True,
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teleop_action_processor=teleop_action_processor,
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robot_action_processor=robot_action_processor,
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robot_observation_processor=robot_observation_processor,
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)
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# Logic for reset env
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# Reset the environment if not stopping or re-recording
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if not events["stop_recording"] and (
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(recorded_episodes < NUM_EPISODES - 1) or events["rerecord_episode"]
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):
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@@ -80,6 +107,9 @@ while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
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control_time_s=RESET_TIME_SEC,
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single_task=TASK_DESCRIPTION,
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display_data=True,
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teleop_action_processor=teleop_action_processor,
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robot_action_processor=robot_action_processor,
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robot_observation_processor=robot_observation_processor,
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)
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if events["rerecord_episode"]:
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@@ -89,13 +119,14 @@ while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
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dataset.clear_episode_buffer()
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continue
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# Save episode
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dataset.save_episode()
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recorded_episodes += 1
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# Upload to hub and clean up
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dataset.push_to_hub()
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# Clean up
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log_say("Stop recording")
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robot.disconnect()
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leader_arm.disconnect()
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keyboard.disconnect()
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listener.stop()
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dataset.push_to_hub()
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