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refactor(cameras): cameras API extension (#2808)
* feat(cameras): add new read_latest() method * fix(cameras): fix threading bug + clear state * refactor(cameras): multiple improvements * feat(camera): add context manager to camera base class * chore(camera): slight modifications to opencv * test(cameras): update opencv tests according to the changes * refactor(cameras): reflect desing changes to realsense + deal with depth * test(cameras): fix realsense tests accordingly to new changes * refactor(cameras): update reachymini and zmq accordingly * chore: wrap resource sensitive examples into a try/finally * test(cameras): add test for new read_latest * test(cameras): fix problem with image artifact in opencv tests * test(cameras): fix test_read_latest_high_frequency expectations * Apply suggestions from code review 1 Co-authored-by: Caroline Pascal <caroline8.pascal@gmail.com> Signed-off-by: Steven Palma <imstevenpmwork@ieee.org> * chore(cameras): address feedback * feat(cameras): add max_age_ms check in read_latest * test(cameras): fix read_latest tests * chore(redundancies): removing redundancies in Reachy 2 camera class * fix(warmup): replacing the arbitrary time.sleep in by an actual warmup in the RealSense camera class * chore(format): formatting latest changes * chore(warning): adding a "to be implemented" warning for read_latest() in Camera base class * chore(warning): making read_latest() warning message shorter and clearer --------- Signed-off-by: Steven Palma <imstevenpmwork@ieee.org> Co-authored-by: Caroline Pascal <caroline8.pascal@gmail.com>
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@@ -81,24 +81,25 @@ def replay(cfg: ReplayConfig):
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actions = dataset.hf_dataset.select_columns(ACTION)
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robot.connect()
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log_say("Replaying episode", cfg.play_sounds, blocking=True)
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for idx in range(dataset.num_frames):
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start_episode_t = time.perf_counter()
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try:
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log_say("Replaying episode", cfg.play_sounds, blocking=True)
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for idx in range(dataset.num_frames):
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start_episode_t = time.perf_counter()
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action_array = actions[idx][ACTION]
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action = {}
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for i, name in enumerate(dataset.features[ACTION]["names"]):
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key = f"{name.removeprefix('main_')}.pos"
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action[key] = action_array[i].item()
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action_array = actions[idx][ACTION]
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action = {}
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for i, name in enumerate(dataset.features[ACTION]["names"]):
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key = f"{name.removeprefix('main_')}.pos"
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action[key] = action_array[i].item()
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action["shoulder_lift.pos"] = -(action["shoulder_lift.pos"] - 90)
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action["elbow_flex.pos"] -= 90
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robot.send_action(action)
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action["shoulder_lift.pos"] = -(action["shoulder_lift.pos"] - 90)
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action["elbow_flex.pos"] -= 90
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robot.send_action(action)
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dt_s = time.perf_counter() - start_episode_t
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precise_sleep(max(1 / dataset.fps - dt_s, 0.0))
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robot.disconnect()
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dt_s = time.perf_counter() - start_episode_t
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precise_sleep(max(1 / dataset.fps - dt_s, 0.0))
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finally:
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robot.disconnect()
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if __name__ == "__main__":
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