feat: Add fixes and refactor lekiwi example (#1396)

* feat: Add fixes and refactor lekiwi example

* fix: replace repo_id with placeholders

* feat: use record_loop for lekiwi, use same control strucutre as record.py

* feat: make rerun log more general for lekiwi

* fix: add comments record_loop and fix params evaluate.py

* fix: add events in evaluate.py

* fix: add events 2

* change record to display data

* Integrate feedback steven

* Add docs merging

* fix: add lekiwi name check

* fix: integrate feedback steven

* fix: list for type

* fix: check type list

* remove second robot connect

* fix: added file when merging

* fix(record): account for edge cases when teleop is a list

---------

Co-authored-by: Steven Palma <steven.palma@huggingface.co>

examples/lekiwi/evaluate.py

@@ -1,32 +1,90 @@
-from lerobot.datasets.utils import build_dataset_frame, hw_to_dataset_features
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+from lerobot.datasets.utils import hw_to_dataset_features
 from lerobot.policies.act.modeling_act import ACTPolicy
+from lerobot.record import record_loop
 from lerobot.robots.lekiwi import LeKiwiClient, LeKiwiClientConfig
-from lerobot.utils.control_utils import predict_action
-from lerobot.utils.utils import get_safe_torch_device
+from lerobot.utils.control_utils import init_keyboard_listener
+from lerobot.utils.utils import log_say
+from lerobot.utils.visualization_utils import _init_rerun
 
-NB_CYCLES_CLIENT_CONNECTION = 1000
+NUM_EPISODES = 2
+FPS = 30
+EPISODE_TIME_SEC = 60
+TASK_DESCRIPTION = "My task description"
 
+# Create the robot and teleoperator configurations
 robot_config = LeKiwiClientConfig(remote_ip="172.18.134.136", id="lekiwi")
 robot = LeKiwiClient(robot_config)
 
+policy = ACTPolicy.from_pretrained("<hf_username>/<policy_repo_id>")
+
+# Configure the dataset features
+action_features = hw_to_dataset_features(robot.action_features, "action")
+obs_features = hw_to_dataset_features(robot.observation_features, "observation")
+dataset_features = {**action_features, **obs_features}
+
+# Create the dataset
+dataset = LeRobotDataset.create(
+    repo_id="<hf_username>/<eval_dataset_repo_id>",
+    fps=FPS,
+    features=dataset_features,
+    robot_type=robot.name,
+    use_videos=True,
+    image_writer_threads=4,
+)
+
+# To connect you already should have this script running on LeKiwi: `python -m lerobot.common.robots.lekiwi.lekiwi_host --robot.id=my_awesome_kiwi`
 robot.connect()
 
-policy = ACTPolicy.from_pretrained("pepijn223/act_lekiwi_circle")
-policy.reset()
+_init_rerun(session_name="recording")
 
-obs_features = hw_to_dataset_features(robot.observation_features, "observation")
+listener, events = init_keyboard_listener()
 
-print("Running inference")
-i = 0
-while i < NB_CYCLES_CLIENT_CONNECTION:
-    obs = robot.get_observation()
+if not robot.is_connected:
+    raise ValueError("Robot is not connected!")
 
-    observation_frame = build_dataset_frame(obs_features, obs, prefix="observation")
-    action_values = predict_action(
-        observation_frame, policy, get_safe_torch_device(policy.config.device), policy.config.use_amp
+recorded_episodes = 0
+while recorded_episodes < NUM_EPISODES and not events["stop_recording"]:
+    log_say(f"Running inference, recording eval episode {recorded_episodes} of {NUM_EPISODES}")
+
+    # Run the policy inference loop
+    record_loop(
+        robot=robot,
+        events=events,
+        fps=FPS,
+        policy=policy,
+        dataset=dataset,
+        control_time_s=EPISODE_TIME_SEC,
+        single_task=TASK_DESCRIPTION,
+        display_data=True,
     )
-    action = {key: action_values[i].item() for i, key in enumerate(robot.action_features)}
-    robot.send_action(action)
-    i += 1
+
+    # Logic for reset env
+    if not events["stop_recording"] and (
+        (recorded_episodes < NUM_EPISODES - 1) or events["rerecord_episode"]
+    ):
+        log_say("Reset the environment")
+        record_loop(
+            robot=robot,
+            events=events,
+            fps=FPS,
+            control_time_s=EPISODE_TIME_SEC,
+            single_task=TASK_DESCRIPTION,
+            display_data=True,
+        )
+
+    if events["rerecord_episode"]:
+        log_say("Re-record episode")
+        events["rerecord_episode"] = False
+        events["exit_early"] = False
+        dataset.clear_episode_buffer()
+        continue
+
+    dataset.save_episode()
+    recorded_episodes += 1
+
+# Upload to hub and clean up
+dataset.push_to_hub()
 
 robot.disconnect()
+listener.stop()