setup robot abstractions and teleop

cameras.py

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+import cv2
+from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig
+from lerobot.cameras.opencv.camera_opencv import OpenCVCamera
+from lerobot.cameras.configs import ColorMode, Cv2Rotation
+
+# First camera
+config1 = OpenCVCameraConfig(
+    index_or_path=0,
+    width=1280,
+    height=720,
+    color_mode=ColorMode.RGB,            # good for ML
+    rotation=Cv2Rotation.NO_ROTATION
+)
+camera1 = OpenCVCamera(config1)
+camera1.connect()
+
+# Second camera
+config2 = OpenCVCameraConfig(
+    index_or_path=3,
+    width=1280,
+    height=720,
+    color_mode=ColorMode.RGB,            # also RGB
+    rotation=Cv2Rotation.ROTATE_180
+)
+camera2 = OpenCVCamera(config2)
+camera2.connect()
+
+try:
+    while True:
+        # Grab latest available frames (non-blocking)
+        frame1 = camera1.async_read()
+        frame2 = camera2.async_read()
+
+        if frame1 is not None:
+            # convert for OpenCV display (expects BGR)
+            cv2.imshow("Camera 0", cv2.cvtColor(frame1, cv2.COLOR_RGB2BGR))
+
+        if frame2 is not None:
+            cv2.imshow("Camera 3", cv2.cvtColor(frame2, cv2.COLOR_RGB2BGR))
+
+        # Needed for display refresh + quit on 'q'
+        if cv2.waitKey(1) & 0xFF == ord("q"):
+            break
+
+finally:
+    camera1.disconnect()
+    camera2.disconnect()
+    cv2.destroyAllWindows()

src/lerobot/robots/meca/collect.py

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+from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+from lerobot.datasets.utils import hw_to_dataset_features
+from lerobot.utils.control_utils import init_keyboard_listener
+from lerobot.utils.utils import log_say
+from lerobot.utils.visualization_utils import init_rerun
+from lerobot.scripts.lerobot_record import record_loop
+
+# Import your robot + teleop
+from lerobot.robots.meca.meca import Meca
+from lerobot.robots.meca.mecaconfig import MecaConfig
+from lerobot.teleoperators.omni.omni import OmniTeleoperator, OmniConfig
+from lerobot.policies.factory import make_policy, make_pre_post_processors
+
+# ------------------------
+# Experiment parameters
+# ------------------------
+NUM_EPISODES = 5
+FPS = 30
+EPISODE_TIME_SEC = 60
+RESET_TIME_SEC = 10
+TASK_DESCRIPTION = "Microsurgery teleop task"
+
+# ------------------------
+# Configurations
+# ------------------------
+
+# Cameras (adapt indices to your setup)
+camera_config = {
+    "top": OpenCVCameraConfig(index_or_path=0, width=640, height=480, fps=FPS),
+    "bottom": OpenCVCameraConfig(index_or_path=3, width=1280, height=720, fps=260),
+}
+
+# Meca robot config
+meca_cfg = MecaConfig(
+    ip="192.168.0.100",       # <-- Replace with your robot IP
+    id="meca500",
+    cameras=camera_config,
+)
+
+# Omni haptic device config
+omni_cfg = OmniConfig()
+
+# ------------------------
+# Instantiate
+# ------------------------
+robot = Meca(meca_cfg)
+teleop = OmniTeleoperator(omni_cfg)
+
+# 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}
+
+
+
+try:
+    dataset = LeRobotDataset("dylanmcguir3/meca-needle-pick")
+    print("📂 Loaded existing dataset")
+except Exception:
+    # Otherwise, create it fresh
+    dataset = LeRobotDataset.create(
+        repo_id="dylanmcguir3/meca-needle-pick",
+        fps=FPS,
+        features=dataset_features,
+        robot_type=robot.name,
+        use_videos=True,
+        image_writer_threads=4,
+    )
+    print("📂 Created new dataset")
+
+# ------------------------
+# Setup utils
+# ------------------------
+_, events = init_keyboard_listener()
+init_rerun(session_name="meca_teleop_recording")
+
+# ------------------------
+# Main recording loop
+# ------------------------
+robot.connect()
+teleop.connect()
+
+episode_idx = 0
+while episode_idx < NUM_EPISODES and not events["stop_recording"]:
+    log_say(f"Recording episode {episode_idx + 1} of {NUM_EPISODES}")
+
+    record_loop(
+        robot=robot,
+        events=events,
+        fps=FPS,
+        teleop=teleop,
+        dataset=dataset,
+        control_time_s=EPISODE_TIME_SEC,
+        single_task=TASK_DESCRIPTION,
+        display_data=True,
+        teleop_action_processor=robot.teleop_action_processor,
+        robot_action_processor=robot.robot_action_processor,
+        robot_observation_processor=robot.robot_observation_processor,
+    )
+
+    # Reset environment if needed
+    if not events["stop_recording"] and (episode_idx < NUM_EPISODES - 1 or events["rerecord_episode"]):
+        log_say("Resetting environment...")
+        record_loop(
+            robot=robot,
+            events=events,
+            fps=FPS,
+            teleop=teleop,
+            control_time_s=RESET_TIME_SEC,
+            single_task=TASK_DESCRIPTION,
+            display_data=True,
+            robot_observation_processor=robot.robot_observation_processor,
+            teleop_action_processor=robot.teleop_action_processor,
+            robot_action_processor=robot.robot_action_processor,
+        )
+
+    if events["rerecord_episode"]:
+        log_say("Re-recording episode")
+        events["rerecord_episode"] = False
+        events["exit_early"] = False
+        dataset.clear_episode_buffer()
+        continue
+
+    dataset.save_episode()
+    episode_idx += 1
+
+# ------------------------
+# Cleanup
+# ------------------------
+log_say("Stopping recording...")
+robot.disconnect()
+teleop.disconnect()
+dataset.push_to_hub()

src/lerobot/robots/meca/inference.py

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+from pathlib import Path
+import time
+
+from lerobot.cameras.opencv.configuration_opencv import OpenCVCameraConfig
+from lerobot.datasets.lerobot_dataset import LeRobotDataset
+from lerobot.datasets.utils import hw_to_dataset_features
+from lerobot.policies.diffusion.modeling_diffusion import DiffusionPolicy
+from lerobot.robots.meca.mecaconfig import MecaConfig
+from lerobot.robots.meca.meca import Meca
+from lerobot.utils.control_utils import init_keyboard_listener
+from lerobot.utils.utils import log_say
+from lerobot.utils.visualization_utils import init_rerun
+from lerobot.scripts.lerobot_record import record_loop
+from lerobot.policies.factory import make_policy, make_pre_post_processors
+import cv2
+
+
+# -------------------------
+# User settings
+# -------------------------
+NUM_EPISODES = 5
+FPS = 30
+EPISODE_TIME_SEC = 60
+TASK_DESCRIPTION = "Microsurgery teleop task"
+
+# 👇 Fill in your actual repos
+HF_USER = "dylanmcguir3"
+HF_MODEL_ID = f"{HF_USER}/needle-pick"        # trained diffusion policy
+HF_DATASET_ID = f"{HF_USER}/meca-needle-pick"        # dataset to store evaluation rollouts
+
+# -------------------------
+# Robot + camera config
+# -------------------------
+camera_config = {
+    "top": OpenCVCameraConfig(index_or_path=0, width=640, height=480, fps=FPS),
+    "bottom": OpenCVCameraConfig(index_or_path=3, width=1280, height=720, fps=260),
+}
+
+robot_config = MecaConfig(ip="192.168.0.100", id="meca_eval_robot", cameras=camera_config)
+robot = Meca(robot_config)
+
+# -------------------------
+# Load trained policy
+# -------------------------
+policy = DiffusionPolicy.from_pretrained(Path("/home/dylan/LeRobot/lerobot/outputs/train/needle-pick-diffusion-test/checkpoints/100000/pretrained_model"))
+
+# -------------------------
+# 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}
+
+dataset = LeRobotDataset.create(
+    repo_id=HF_DATASET_ID + "-eval",
+    fps=FPS,
+    features=dataset_features,
+    robot_type=robot.name,
+    use_videos=True,
+    image_writer_threads=4,
+)
+
+# -------------------------
+# Keyboard + visualization
+# -------------------------
+_, events = init_keyboard_listener()
+init_rerun(session_name="policy_eval")
+
+# -------------------------
+# Connect robot
+# -------------------------
+robot.connect()
+
+# Pre/post processors for policy I/O
+preprocessor, postprocessor = make_pre_post_processors(policy, pretrained_path=Path("/home/dylan/LeRobot/lerobot/outputs/train/needle-pick-diffusion-test/checkpoints/100000/pretrained_model"), dataset_stats=dataset.meta.stats)
+
+# -------------------------
+# Evaluation loop
+# -------------------------
+for episode_idx in range(NUM_EPISODES):
+    log_say(f"Running inference, recording eval episode {episode_idx + 1}/{NUM_EPISODES}")
+
+    record_loop(
+        robot=robot,
+        events=events,
+        fps=FPS,
+        policy=policy,
+        preprocessor=preprocessor,
+        postprocessor=postprocessor,
+        dataset=dataset,
+        control_time_s=EPISODE_TIME_SEC,
+        single_task=TASK_DESCRIPTION,
+        display_data=True,
+        teleop_action_processor=robot.teleop_action_processor,
+        robot_action_processor=robot.robot_action_processor,
+        robot_observation_processor=robot.robot_observation_processor,
+    )
+
+    if cv2.waitKey(1) & 0xFF == ord("r"):
+        robot.reset()
+
+
+    dataset.save_episode()
+
+# -------------------------
+# Cleanup
+# -------------------------
+robot.disconnect()
+dataset.push_to_hub()