diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..614a4cd3297ee019522ada0a8b42ea21a274da69 --- /dev/null +++ b/LICENSE @@ -0,0 +1,30 @@ +BSD 3-Clause License + +Copyright (c) 2026, LxRoboticsLab +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +3. Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +POSSIBILITY OF SUCH DAMAGE. diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..f2750ca97b414ad200d4b55b40e8a86ba8cf1a9e --- /dev/null +++ b/README.md @@ -0,0 +1,255 @@ +--- +language: +- en +- zh +license: bsd-3-clause +pretty_name: ReflexBench Simulation Task Examples +configs: +- config_name: all + data_files: + - split: examples + path: data/all.parquet + default: true +- config_name: task_000000 + data_files: + - split: examples + path: data/task_000000.parquet +- config_name: task_000001 + data_files: + - split: examples + path: data/task_000001.parquet +- config_name: task_000002 + data_files: + - split: examples + path: data/task_000002.parquet +- config_name: task_000003 + data_files: + - split: examples + path: data/task_000003.parquet +- config_name: task_000004 + data_files: + - split: examples + path: data/task_000004.parquet +- config_name: task_000005 + data_files: + - split: examples + path: data/task_000005.parquet +- config_name: reaction_critical + data_files: + - split: examples + path: data/reaction_critical.parquet +tags: +- robotics +- video +- simulation +--- +# ReflexBench Simulation Task Examples + +[打开 MP4 任务浏览页](https://travor278-reflexbench-task-examples.static.hf.space/?task=0) + +Six official task_index values 0–5. Single Franka arm; only fixed_cam and wrist_cam exist. Do not relabel the wrist as left/right. Success rules describe evaluation, not an unprovided per-demo score. + +所有示例是完整 H.264 MP4。单臂相机保留官方名称：fixed_cam / wrist_cam。每条有同步合并视频、各路原视频与官方动作/状态 Parquet。 + +评估标准根据官方代码和文档整理；发布数据未保存逐条示教 success 标签，故 actual_episode_success 为 null。本文不编造 0–100 得分。 + +| 官方 task_index | Task / instruction scenario | 分类 | 直接浏览 | +|---|---|---|---| +| 0 | Ball Catching | Reaction-critical | [打开](https://travor278-reflexbench-task-examples.static.hf.space/?task=0) | +| 1 | Conveyor Belt Pick And Place | Reaction-critical | [打开](https://travor278-reflexbench-task-examples.static.hf.space/?task=1) | +| 2 | Whack A Mole | Reaction-critical | [打开](https://travor278-reflexbench-task-examples.static.hf.space/?task=2) | +| 3 | Rolling Ball Interception | Reaction-critical | [打开](https://travor278-reflexbench-task-examples.static.hf.space/?task=3) | +| 4 | Ball Throwing | Reaction-critical | [打开](https://travor278-reflexbench-task-examples.static.hf.space/?task=4) | +| 5 | Rotating Peg Insertion | Reaction-critical | [打开](https://travor278-reflexbench-task-examples.static.hf.space/?task=5) | + +## task_index=0 · Ball Catching + +**Instruction:** hold the container with the gripper and catch the thrown ball in the container + +**Description:** Catch a launched ball with a held container. + +**Success / evaluation:** Episode success is task_phase == 4. The ball must remain in the virtual catch zone below the end effector for the configured consecutive-step threshold. + +[官方说明](https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/ball_catching/README.md) + +**Gym ID:** `BallCatching-Franka-DataCollection-v0` + +**episode_index=0** · 24 frames / 0.96 s + +![Camera preview](media/ball_catching/episode_000000/preview.jpg) + +[同步 MP4](media/ball_catching/episode_000000/synchronized.mp4) · [fixed_cam MP4](media/ball_catching/episode_000000/fixed_cam.mp4) · [wrist_cam MP4](media/ball_catching/episode_000000/wrist_cam.mp4) · [官方轨迹](trajectories/ball_catching/episode_000000.parquet) + +**episode_index=100** · 27 frames / 1.08 s + +![Camera preview](media/ball_catching/episode_000100/preview.jpg) + +[同步 MP4](media/ball_catching/episode_000100/synchronized.mp4) · [fixed_cam MP4](media/ball_catching/episode_000100/fixed_cam.mp4) · [wrist_cam MP4](media/ball_catching/episode_000100/wrist_cam.mp4) · [官方轨迹](trajectories/ball_catching/episode_000100.parquet) + +**episode_index=199** · 37 frames / 1.48 s + +![Camera preview](media/ball_catching/episode_000199/preview.jpg) + +[同步 MP4](media/ball_catching/episode_000199/synchronized.mp4) · [fixed_cam MP4](media/ball_catching/episode_000199/fixed_cam.mp4) · [wrist_cam MP4](media/ball_catching/episode_000199/wrist_cam.mp4) · [官方轨迹](trajectories/ball_catching/episode_000199.parquet) + +## task_index=1 · Conveyor Belt Pick And Place + +**Instruction:** pick up the cube from the moving conveyor and place it into the bin + +**Description:** Pick from the moving conveyor and release into the bin. + +**Success / evaluation:** Success requires the object inside the bin in environment-local coordinates: x in [-0.2,0.2], y in [-0.6,-0.3], z in [0.0,0.08] m. + +[官方说明](https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/conveyor_belt_pick_and_place/README.md) + +**Gym ID:** `ConveyorBeltPickAndPlace-Franka-DataCollection-v0` + +**episode_index=200** · 31 frames / 1.24 s + +![Camera preview](media/conveyor_belt_pick_and_place/episode_000200/preview.jpg) + +[同步 MP4](media/conveyor_belt_pick_and_place/episode_000200/synchronized.mp4) · [fixed_cam MP4](media/conveyor_belt_pick_and_place/episode_000200/fixed_cam.mp4) · [wrist_cam MP4](media/conveyor_belt_pick_and_place/episode_000200/wrist_cam.mp4) · [官方轨迹](trajectories/conveyor_belt_pick_and_place/episode_000200.parquet) + +**episode_index=318** · 37 frames / 1.48 s + +![Camera preview](media/conveyor_belt_pick_and_place/episode_000318/preview.jpg) + +[同步 MP4](media/conveyor_belt_pick_and_place/episode_000318/synchronized.mp4) · [fixed_cam MP4](media/conveyor_belt_pick_and_place/episode_000318/fixed_cam.mp4) · [wrist_cam MP4](media/conveyor_belt_pick_and_place/episode_000318/wrist_cam.mp4) · [官方轨迹](trajectories/conveyor_belt_pick_and_place/episode_000318.parquet) + +**episode_index=435** · 36 frames / 1.44 s + +![Camera preview](media/conveyor_belt_pick_and_place/episode_000435/preview.jpg) + +[同步 MP4](media/conveyor_belt_pick_and_place/episode_000435/synchronized.mp4) · [fixed_cam MP4](media/conveyor_belt_pick_and_place/episode_000435/fixed_cam.mp4) · [wrist_cam MP4](media/conveyor_belt_pick_and_place/episode_000435/wrist_cam.mp4) · [官方轨迹](trajectories/conveyor_belt_pick_and_place/episode_000435.parquet) + +## task_index=2 · Whack A Mole + +**Instruction:** hit the mole that pops up on the board with the closed gripper + +**Description:** Strike the active mole using the closed gripper during its popup window. + +**Success / evaluation:** Unified evaluation success is valid_hits > 0. A valid hit requires proximity to the active mole, closed gripper and the configured dwell. Current eval profile uses 2.0 s popup, 0.3 s gap, 0 s initial delay and 3.0 s evaluation length. Completing the window schedule alone is not success. + +[官方说明](https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/whack_a_mole/README.md) + +**Gym ID:** `WhackAMole-Franka-DataCollection-v0` + +**episode_index=436** · 18 frames / 0.72 s + +![Camera preview](media/whack_a_mole/episode_000436/preview.jpg) + +[同步 MP4](media/whack_a_mole/episode_000436/synchronized.mp4) · [fixed_cam MP4](media/whack_a_mole/episode_000436/fixed_cam.mp4) · [wrist_cam MP4](media/whack_a_mole/episode_000436/wrist_cam.mp4) · [官方轨迹](trajectories/whack_a_mole/episode_000436.parquet) + +**episode_index=536** · 16 frames / 0.64 s + +![Camera preview](media/whack_a_mole/episode_000536/preview.jpg) + +[同步 MP4](media/whack_a_mole/episode_000536/synchronized.mp4) · [fixed_cam MP4](media/whack_a_mole/episode_000536/fixed_cam.mp4) · [wrist_cam MP4](media/whack_a_mole/episode_000536/wrist_cam.mp4) · [官方轨迹](trajectories/whack_a_mole/episode_000536.parquet) + +**episode_index=635** · 16 frames / 0.64 s + +![Camera preview](media/whack_a_mole/episode_000635/preview.jpg) + +[同步 MP4](media/whack_a_mole/episode_000635/synchronized.mp4) · [fixed_cam MP4](media/whack_a_mole/episode_000635/fixed_cam.mp4) · [wrist_cam MP4](media/whack_a_mole/episode_000635/wrist_cam.mp4) · [官方轨迹](trajectories/whack_a_mole/episode_000635.parquet) + +## task_index=3 · Rolling Ball Interception + +**Instruction:** hold the container with the gripper and catch the orange rolling down the ramp in the container + +**Description:** Intercept the ball or orange rolling down the ramp. + +**Success / evaluation:** Episode success is task_phase == 4. The rolling object must stay in the virtual catch zone for the configured hold threshold. + +[官方说明](https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/rolling_ball_interception/README.md) + +**Gym ID:** `RollingBallInterception-Franka-DataCollection-v0` + +**episode_index=636** · 26 frames / 1.04 s + +![Camera preview](media/rolling_ball_interception/episode_000636/preview.jpg) + +[同步 MP4](media/rolling_ball_interception/episode_000636/synchronized.mp4) · [fixed_cam MP4](media/rolling_ball_interception/episode_000636/fixed_cam.mp4) · [wrist_cam MP4](media/rolling_ball_interception/episode_000636/wrist_cam.mp4) · [官方轨迹](trajectories/rolling_ball_interception/episode_000636.parquet) + +**episode_index=736** · 26 frames / 1.04 s + +![Camera preview](media/rolling_ball_interception/episode_000736/preview.jpg) + +[同步 MP4](media/rolling_ball_interception/episode_000736/synchronized.mp4) · [fixed_cam MP4](media/rolling_ball_interception/episode_000736/fixed_cam.mp4) · [wrist_cam MP4](media/rolling_ball_interception/episode_000736/wrist_cam.mp4) · [官方轨迹](trajectories/rolling_ball_interception/episode_000736.parquet) + +**episode_index=835** · 26 frames / 1.04 s + +![Camera preview](media/rolling_ball_interception/episode_000835/preview.jpg) + +[同步 MP4](media/rolling_ball_interception/episode_000835/synchronized.mp4) · [fixed_cam MP4](media/rolling_ball_interception/episode_000835/fixed_cam.mp4) · [wrist_cam MP4](media/rolling_ball_interception/episode_000835/wrist_cam.mp4) · [官方轨迹](trajectories/rolling_ball_interception/episode_000835.parquet) + +## task_index=4 · Ball Throwing + +**Instruction:** toss the ball into the bin + +**Description:** Throw the pre-grasped ball into the target bin. + +**Success / evaluation:** Success is task_phase == 2, meaning the ball entered the target bin. Documentation bounds relative to bin center: |x-cx| <= 0.13, |y-cy| <= 0.09, z in [0.02,0.18] m. + +[官方说明](https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/ball_throwing/README.md) + +**Gym ID:** `BallThrowing-Franka-DataCollection-v0` + +**episode_index=836** · 33 frames / 1.32 s + +![Camera preview](media/ball_throwing/episode_000836/preview.jpg) + +[同步 MP4](media/ball_throwing/episode_000836/synchronized.mp4) · [fixed_cam MP4](media/ball_throwing/episode_000836/fixed_cam.mp4) · [wrist_cam MP4](media/ball_throwing/episode_000836/wrist_cam.mp4) · [官方轨迹](trajectories/ball_throwing/episode_000836.parquet) + +**episode_index=936** · 35 frames / 1.40 s + +![Camera preview](media/ball_throwing/episode_000936/preview.jpg) + +[同步 MP4](media/ball_throwing/episode_000936/synchronized.mp4) · [fixed_cam MP4](media/ball_throwing/episode_000936/fixed_cam.mp4) · [wrist_cam MP4](media/ball_throwing/episode_000936/wrist_cam.mp4) · [官方轨迹](trajectories/ball_throwing/episode_000936.parquet) + +**episode_index=1035** · 33 frames / 1.32 s + +![Camera preview](media/ball_throwing/episode_001035/preview.jpg) + +[同步 MP4](media/ball_throwing/episode_001035/synchronized.mp4) · [fixed_cam MP4](media/ball_throwing/episode_001035/fixed_cam.mp4) · [wrist_cam MP4](media/ball_throwing/episode_001035/wrist_cam.mp4) · [官方轨迹](trajectories/ball_throwing/episode_001035.parquet) + +## task_index=5 · Rotating Peg Insertion + +**Instruction:** insert the peg into the hole on the rotating disc + +**Description:** Time peg insertion into the moving hole of a rotating disc. + +**Success / evaluation:** Success is task_phase == 4. Peg tip enters the hole within its radius tolerance, descends at least 0.02 m below the disc surface, and holds for at least 5 control steps (task README). + +[官方说明](https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/rotating_peg_insertion/README.md) + +**Gym ID:** `RotatingPegInsertion-Franka-DataCollection-v0` + +**episode_index=1036** · 28 frames / 1.12 s + +![Camera preview](media/rotating_peg_insertion/episode_001036/preview.jpg) + +[同步 MP4](media/rotating_peg_insertion/episode_001036/synchronized.mp4) · [fixed_cam MP4](media/rotating_peg_insertion/episode_001036/fixed_cam.mp4) · [wrist_cam MP4](media/rotating_peg_insertion/episode_001036/wrist_cam.mp4) · [官方轨迹](trajectories/rotating_peg_insertion/episode_001036.parquet) + +**episode_index=1136** · 59 frames / 2.36 s + +![Camera preview](media/rotating_peg_insertion/episode_001136/preview.jpg) + +[同步 MP4](media/rotating_peg_insertion/episode_001136/synchronized.mp4) · [fixed_cam MP4](media/rotating_peg_insertion/episode_001136/fixed_cam.mp4) · [wrist_cam MP4](media/rotating_peg_insertion/episode_001136/wrist_cam.mp4) · [官方轨迹](trajectories/rotating_peg_insertion/episode_001136.parquet) + +**episode_index=1235** · 34 frames / 1.36 s + +![Camera preview](media/rotating_peg_insertion/episode_001235/preview.jpg) + +[同步 MP4](media/rotating_peg_insertion/episode_001235/synchronized.mp4) · [fixed_cam MP4](media/rotating_peg_insertion/episode_001235/fixed_cam.mp4) · [wrist_cam MP4](media/rotating_peg_insertion/episode_001235/wrist_cam.mp4) · [官方轨迹](trajectories/rotating_peg_insertion/episode_001235.parquet) + +## 来源、许可与复现 + +官方数据：[原仓库](https://huggingface.co/datasets/cyx337/ReflexBench_dataset) · 固定 revision `9295b6e9878609a992047f0b8b65421a493299e7`。 + +官方代码：[GitHub](https://github.com/LxRoboticsLab/ReflexBench) · revision `8bb931485093c6d98f8729774ad01bf824964e16`。 + +保留上游 LICENSE 和来源文件在 `reference/`。ReflexBench 官方数据未单列许可证元数据；保留官方实现 BSD-3-Clause 来源，不扩大作者权利。 + +选择性提取记录、原始时间区间、task/episode 对应、相机元数据和校验均在 `provenance/`。不下载场景资产、模型权重或完整数据仓库。 + +复现脚本：`scripts/build_examples.py`。浏览页源码另见 `browser/` 和 `scripts/build_browser.py`。 diff --git a/data/all.parquet b/data/all.parquet new file mode 100644 index 0000000000000000000000000000000000000000..975ef20788020b8263b8a96264fbb3fd44279d7b --- /dev/null +++ b/data/all.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b70f0c7d5f7e83f1e70f5d68cff8e5afcda22014475ffaf8361a9ad358d8c75c +size 21808 diff --git a/data/reaction_critical.parquet b/data/reaction_critical.parquet new file mode 100644 index 0000000000000000000000000000000000000000..975ef20788020b8263b8a96264fbb3fd44279d7b --- /dev/null +++ b/data/reaction_critical.parquet @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b70f0c7d5f7e83f1e70f5d68cff8e5afcda22014475ffaf8361a9ad358d8c75c +size 21808 diff --git 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Single Franka arm; only fixed_cam and wrist_cam exist. Do not relabel the wrist as left/right. Success rules describe evaluation, not an unprovided per-demo score.", + "date": "2026-10-03", + "video_policy": "Complete selected episodes, converted to browser-friendly H.264 MP4 at original 25 FPS. No generated simulation rollouts.", + "actual_episode_score": "Not published in released LeRobot features; null, not assumed successful.", + "episode_selection": "First/middle/last episode per official task", + "camera_order": [ + "fixed_cam", + "wrist_cam" + ] +} \ No newline at end of file diff --git a/provenance/tasks.json b/provenance/tasks.json new file mode 100644 index 0000000000000000000000000000000000000000..2ae53d58bedf9310718d9c6aaddf979b91dd3715 --- /dev/null +++ b/provenance/tasks.json @@ -0,0 +1,173 @@ +[ + { + "task_index": 0, + "key": "ball_catching", + "name": "Ball Catching", + "category": "Reaction-critical", + "instruction": "hold the container with the gripper and catch the thrown ball in the container", + "description": "Catch a launched ball with a held container.", + "success_rule": "Episode success is task_phase == 4. The ball must remain in the virtual catch zone below the end effector for the configured consecutive-step threshold.", + "profile": { + "gym_id": "BallCatching-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": false, + "short_circuit_success": true, + "success_type": "task_phase_4", + "phase_names": { + "0": "wait", + "1": "launch", + "2": "predict", + "3": "position", + "4": "catch" + } + }, + "official_gym_id": "BallCatching-Franka-DataCollection-v0", + "doc_url": "https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/ball_catching/README.md", + "published_episode_count": 200 + }, + { + "task_index": 1, + "key": "conveyor_belt_pick_and_place", + "name": "Conveyor Belt Pick And Place", + "category": "Reaction-critical", + "instruction": "pick up the cube from the moving conveyor and place it into the bin", + "description": "Pick from the moving conveyor and release into the bin.", + "success_rule": "Success requires the object inside the bin in environment-local coordinates: x in [-0.2,0.2], y in [-0.6,-0.3], z in [0.0,0.08] m.", + "profile": { + "gym_id": "ConveyorBeltPickAndPlace-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": true, + "short_circuit_success": true, + "success_type": "object_in_box", + "phase_names": { + "0": "approach", + "1": "lift", + "2": "transport", + "3": "release", + "4": "return", + "5": "done" + }, + "box_x_range": [ + -0.2, + 0.2 + ], + "box_y_range": [ + -0.6, + -0.3 + ], + "box_z_range": [ + 0.0, + 0.08 + ] + }, + "official_gym_id": "ConveyorBeltPickAndPlace-Franka-DataCollection-v0", + "doc_url": "https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/conveyor_belt_pick_and_place/README.md", + "published_episode_count": 236 + }, + { + "task_index": 2, + "key": "whack_a_mole", + "name": "Whack A Mole", + "category": "Reaction-critical", + "instruction": "hit the mole that pops up on the board with the closed gripper", + "description": "Strike the active mole using the closed gripper during its popup window.", + "success_rule": "Unified evaluation success is valid_hits > 0. A valid hit requires proximity to the active mole, closed gripper and the configured dwell. Current eval profile uses 2.0 s popup, 0.3 s gap, 0 s initial delay and 3.0 s evaluation length. Completing the window schedule alone is not success.", + "profile": { + "gym_id": "WhackAMole-Franka-DataCollection-v0", + "action_scale": 0.2, + "has_ik_override": false, + "short_circuit_success": false, + "success_type": "whack_a_mole", + "popup_duration_s": 2.0, + "popup_gap_s": 0.3, + "popup_initial_delay_s": 0.0, + "eval_episode_length_s": 3.0, + "phase_names": { + "0": "wait popup", + "1": "move", + "2": "strike", + "3": "return", + "4": "done" + } + }, + "official_gym_id": "WhackAMole-Franka-DataCollection-v0", + "doc_url": "https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/whack_a_mole/README.md", + "published_episode_count": 200 + }, + { + "task_index": 3, + "key": "rolling_ball_interception", + "name": "Rolling Ball Interception", + "category": "Reaction-critical", + "instruction": "hold the container with the gripper and catch the orange rolling down the ramp in the container", + "description": "Intercept the ball or orange rolling down the ramp.", + "success_rule": "Episode success is task_phase == 4. The rolling object must stay in the virtual catch zone for the configured hold threshold.", + "profile": { + "gym_id": "RollingBallInterception-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": false, + "short_circuit_success": true, + "success_type": "task_phase_4", + "phase_names": { + "0": "wait", + "1": "roll", + "2": "predict", + "3": "position", + "4": "catch" + } + }, + "official_gym_id": "RollingBallInterception-Franka-DataCollection-v0", + "doc_url": "https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/rolling_ball_interception/README.md", + "published_episode_count": 200 + }, + { + "task_index": 4, + "key": "ball_throwing", + "name": "Ball Throwing", + "category": "Reaction-critical", + "instruction": "toss the ball into the bin", + "description": "Throw the pre-grasped ball into the target bin.", + "success_rule": "Success is task_phase == 2, meaning the ball entered the target bin. Documentation bounds relative to bin center: |x-cx| <= 0.13, |y-cy| <= 0.09, z in [0.02,0.18] m.", + "profile": { + "gym_id": "BallThrowing-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": false, + "short_circuit_success": true, + "success_type": "task_phase_2", + "phase_names": { + "0": "swing", + "1": "release", + "2": "in box" + } + }, + "official_gym_id": "BallThrowing-Franka-DataCollection-v0", + "doc_url": "https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/ball_throwing/README.md", + "published_episode_count": 200 + }, + { + "task_index": 5, + "key": "rotating_peg_insertion", + "name": "Rotating Peg Insertion", + "category": "Reaction-critical", + "instruction": "insert the peg into the hole on the rotating disc", + "description": "Time peg insertion into the moving hole of a rotating disc.", + "success_rule": "Success is task_phase == 4. Peg tip enters the hole within its radius tolerance, descends at least 0.02 m below the disc surface, and holds for at least 5 control steps (task README).", + "profile": { + "gym_id": "RotatingPegInsertion-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": false, + "short_circuit_success": true, + "success_type": "task_phase_4", + "phase_names": { + "0": "pre-align", + "1": "track", + "2": "wait alignment", + "3": "insert", + "4": "done" + } + }, + "official_gym_id": "RotatingPegInsertion-Franka-DataCollection-v0", + "doc_url": "https://github.com/LxRoboticsLab/ReflexBench/blob/8bb931485093c6d98f8729774ad01bf824964e16/source/reflexbench/reflexbench/tasks/manager_based/rotating_peg_insertion/README.md", + "published_episode_count": 200 + } +] \ No newline at end of file diff --git a/provenance/validation.json b/provenance/validation.json new file mode 100644 index 0000000000000000000000000000000000000000..309ed27c85a772a17d91df30dd49094cb2b78f5c --- /dev/null +++ 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"1.360000", + "nb_frames": "34" + }, + { + "path": "media/rotating_peg_insertion/episode_001235/synchronized.mp4", + "codec_name": "h264", + "width": 640, + "height": 348, + "duration": "1.360000", + "nb_frames": "34" + } + ] + } + ] +} \ No newline at end of file diff --git a/reference/LICENSE b/reference/LICENSE new file mode 100644 index 0000000000000000000000000000000000000000..614a4cd3297ee019522ada0a8b42ea21a274da69 --- /dev/null +++ b/reference/LICENSE @@ -0,0 +1,30 @@ +BSD 3-Clause License + +Copyright (c) 2026, LxRoboticsLab +All rights reserved. + +Redistribution and use in source and binary forms, with or without +modification, are permitted provided that the following conditions are met: + +1. Redistributions of source code must retain the above copyright notice, + this list of conditions and the following disclaimer. + +2. Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + +3. Neither the name of the copyright holder nor the names of its + contributors may be used to endorse or promote products derived from + this software without specific prior written permission. + +THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" +AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE +IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE +ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE +LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR +CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF +SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS +INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN +CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) +ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE +POSSIBILITY OF SUCH DAMAGE. diff --git a/reference/README.md b/reference/README.md new file mode 100644 index 0000000000000000000000000000000000000000..a98022cf575db144f21b449d1c0185df8a4862dc --- /dev/null +++ b/reference/README.md @@ -0,0 +1,450 @@ +# ReflexBench + +Official Isaac Lab implementation of **ReflexBench**, the reaction-critical manipulation benchmark introduced in [*Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation*](https://arxiv.org/abs/2608.14379). + +ReflexBench contains six dynamic manipulation tasks and a latency-aware evaluation framework. Simulator stepping is decoupled from robot control, allowing controlled evaluation of synchronous and asynchronous policy inference at configurable control frequencies and inference latencies. + +- Paper: https://arxiv.org/abs/2608.14379 +- Project page: https://reflexvla.github.io +- Dataset: https://huggingface.co/datasets/cyx337/ReflexBench_dataset +- Repository: https://github.com/LxRoboticsLab/ReflexBench + +## Tasks + +Each task provides joint-position, absolute-IK, relative-IK, play, and camera-enabled data-collection variants. + +| Task | Gym ID prefix | Demonstration policy | Source | +| --- | --- | --- | --- | +| Conveyor Belt Pick-and-Place | `ConveyorBeltPickAndPlace-Franka` | RL checkpoint | [task](source/reflexbench/reflexbench/tasks/manager_based/conveyor_belt_pick_and_place/README.md) | +| Ball Catching | `BallCatching-Franka` | Planning | [task](source/reflexbench/reflexbench/tasks/manager_based/ball_catching/README.md) | +| Whack-a-Mole | `WhackAMole-Franka` | Planning | [task](source/reflexbench/reflexbench/tasks/manager_based/whack_a_mole/README.md) | +| Rolling Ball Interception | `RollingBallInterception-Franka` | Planning | [task](source/reflexbench/reflexbench/tasks/manager_based/rolling_ball_interception/README.md) | +| Ball Throwing | `BallThrowing-Franka` | Planning | [task](source/reflexbench/reflexbench/tasks/manager_based/ball_throwing/README.md) | +| Rotating Peg Insertion | `RotatingPegInsertion-Franka` | Planning | [task](source/reflexbench/reflexbench/tasks/manager_based/rotating_peg_insertion/README.md) | + +Task suffixes follow this convention: + +| Suffix | Control / purpose | +| --- | --- | +| `-v0` | Joint-position control | +| `-Play-v0` | Lightweight play/evaluation configuration | +| `-IK-Abs-v0` | Absolute end-effector pose control | +| `-IK-Rel-v0` | Relative end-effector pose control | +| `-DataCollection-v0` | Camera-enabled VLA data collection and evaluation | + +Run `python scripts/list_envs.py` after installation to list every registered ID. + +### Control and observation representations + +Data collection and evaluation use the same `--control` setting so the controller, recorded actions, and policy outputs remain consistent. + +| `--control` | Action format | Dimension | Default proprioception with `--state_format auto` | +| --- | --- | ---: | --- | +| `joint_pos` | Seven absolute arm-joint targets and gripper | 8 | Joint positions and gripper state | +| `ik_abs` | Absolute end-effector position and roll-pitch-yaw, plus gripper | 7 | End-effector position, quaternion, and gripper state | +| `ik_rel` | Relative end-effector position and roll-pitch-yaw delta, plus gripper | 7 | End-effector position, quaternion, and gripper state | + +End-effector orientations in observations use quaternion order `(w, x, y, z)` by default. IK action orientations use roll-pitch-yaw. Evaluation can override proprioception with `--state_format joint`, `eef_pose`, or `both`, and orientation with `--orientation_rep quat` or `euler`. + +## Installation + +1. Install [Isaac Lab](https://isaac-sim.github.io/IsaacLab/main/source/setup/installation/index.html) and activate its Python environment. +2. Clone ReflexBench outside the Isaac Lab source directory. +3. Install the extension: + + ```bash + git clone https://github.com/LxRoboticsLab/ReflexBench.git + cd ReflexBench + python -m pip install -e source/reflexbench + ``` + + Install the optional LeRobot conversion tools with: + + ```bash + python -m pip install -e "source/reflexbench[data]" + ``` + + The planning-based collectors for five tasks additionally require [cuRobo](https://curobo.org) in the Isaac Lab environment. Conveyor Belt Pick-and-Place uses an RL checkpoint instead. + +4. Verify task registration: + + ```bash + python scripts/list_envs.py + python scripts/zero_agent.py --task BallCatching-Franka-Play-v0 + ``` + +## Data collection + +`collect_vla_data.py` records synchronized camera observations, robot state, actions, task metadata, and success labels to HDF5. + +**Conveyor Belt Pick-and-Place is currently the only task whose demonstration collection depends on a trained RL policy. It does not support `--policy planning`.** The other five tasks use their task-specific planning policies. All examples use `DataCollection-v0` variants because those variants enable the fixed and wrist cameras. + +### Released LeRobot v3.0 dataset + +A curated version of the ReflexBench demonstrations is available on Hugging Face at [`cyx337/ReflexBench_dataset`](https://huggingface.co/datasets/cyx337/ReflexBench_dataset). The dataset uses the **LeRobot v3.0** format and contains approximately **200 episodes per task** for all six ReflexBench tasks. + +Download the complete dataset with the Hugging Face CLI: + +```bash +hf download cyx337/ReflexBench_dataset \ + --type dataset \ + --local-dir datasets/ReflexBench_dataset +``` + +### Conveyor Belt Pick-and-Place + +#### Train the RL policy + +The data collector currently loads skrl checkpoints. Train the PPO policy with: + +```bash +python scripts/skrl/train.py \ + --task ConveyorBeltPickAndPlace-Franka-v0 \ + --headless +``` + +Training outputs are written below `logs/skrl/logs/conveyor_belt_pick_and_place/`. To inspect a checkpoint before collecting data: + +```bash +python scripts/skrl/play.py \ + --task ConveyorBeltPickAndPlace-Franka-Play-v0 \ + --checkpoint /path/to/conveyor_policy.pt +``` + +An RSL-RL training configuration is also registered for RL experiments: + +```bash +python scripts/rsl_rl/train.py \ + --task ConveyorBeltPickAndPlace-Franka-v0 \ + --headless +``` + +RSL-RL checkpoints are not currently accepted by `collect_vla_data.py`; use a skrl checkpoint for demonstration collection. + +#### Collect demonstrations with the RL checkpoint + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task ConveyorBeltPickAndPlace-Franka-DataCollection-v0 \ + --policy checkpoint \ + --checkpoint /path/to/conveyor_policy.pt \ + --control joint_pos \ + --num_envs 5 \ + --num_episodes 200 \ + --headless +``` + +The checkpoint and `--control` mode must match the environment used during RL training. Passing `--policy planning` for this task is rejected explicitly. + +### Ball Catching + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task BallCatching-Franka-DataCollection-v0 \ + --policy planning \ + --control joint_pos \ + --num_envs 5 \ + --num_episodes 200 \ + --planning_speed 4.0 \ + --headless +``` + +### Whack-a-Mole + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task WhackAMole-Franka-DataCollection-v0 \ + --policy planning \ + --control joint_pos \ + --num_envs 5 \ + --num_episodes 10 \ + --planning_speed 4.0 \ + --headless +``` + +### Rolling Ball Interception + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task RollingBallInterception-Franka-DataCollection-v0 \ + --policy planning \ + --control joint_pos \ + --num_envs 5 \ + --num_episodes 10 \ + --planning_speed 4.0 \ + --headless +``` + +### Ball Throwing + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task BallThrowing-Franka-DataCollection-v0 \ + --policy planning \ + --control joint_pos \ + --num_envs 5 \ + --num_episodes 200 \ + --headless +``` + +### Rotating Peg Insertion + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task RotatingPegInsertion-Franka-DataCollection-v0 \ + --policy planning \ + --control joint_pos \ + --num_envs 5 \ + --num_episodes 200 \ + --planning_speed 4.0 \ + --headless +``` + +Important collection options: + +- `--num_envs` is the number of parallel simulation environments. +- `--num_episodes` is the total number of saved episodes, not the number per environment. +- `--planning_speed 4.0` shortens planned trajectories for the five planning-supported tasks; it does not apply to Conveyor Belt Pick-and-Place. +- `--save_failed` retains failed episodes; without it, only successful episodes are saved. +- `--fps` overrides both the robot control rate and dataset FPS while leaving the physics timestep unchanged. +- `--prompt` overrides the task-specific language instruction stored in the dataset. +- `--output` selects an explicit HDF5 path. If omitted, the collector writes under `scripts/data_collection/collected_data//`. +- `--control` must match the policy action representation. `joint_pos` uses 8 values (7 arm joints and gripper); either IK mode uses 7 values (6-DoF end-effector command and gripper). + +### Convert HDF5 to LeRobot + +For example, the default Ball Catching collection path can be converted with: + +```bash +python scripts/data_collection/convert_to_lerobot.py \ + --input scripts/data_collection/collected_data/ballcatching/ballcatching_franka_datacollection_v0.hdf5 \ + --output datasets/ballcatching +``` + +Useful conversion options: + +- `--target_fps x` downsamples the source trajectories to x FPS. +- `--success_only` skips episodes not marked successful. +- `--output` may be an absolute path when the LeRobot dataset should live outside this repository. + +The converter reads the task, cameras, FPS, state representation, action representation, and language prompt from the HDF5 metadata. + +## Latency-aware evaluation + +`scripts/evaluation/eval.py` supports a remote policy server and a local ACT checkpoint. The remote server must implement the [policy-server protocol](scripts/evaluation/POLICY_SERVER.md). + +### Evaluate your own policy + +The recommended way to evaluate a custom policy is to wrap its inference code in an HTTP server. This keeps model-specific dependencies separate from the Isaac Lab environment and supports policies implemented with any framework. Follow [`scripts/evaluation/POLICY_SERVER.md`](scripts/evaluation/POLICY_SERVER.md) for the complete request and response schemas and a minimal FastAPI example. + +The evaluation client uses these endpoints: + +| Endpoint | Required | Purpose | +| --- | --- | --- | +| `GET /info` | Yes | Report `action_dim`, `action_horizon`, model name, and control mode. | +| `POST /predict` | Yes | Receive a batched observation and return one action chunk per environment. | +| `POST /reset` | No | Clear recurrent state or observation history for environments that have reset. | + +A typical integration workflow is: + +1. Load your policy and preprocessing pipeline in a server process. +2. Implement `/info` and `/predict` according to the policy-server protocol. The `actions` response should normally have shape `(N, H, D)`, where `N` is the requested number of environments, `H` is the action horizon, and `D` is the action dimension. +3. If the policy keeps temporal state, implement `/reset` and clear only the environment IDs included in the request. +4. Start the server and verify its metadata endpoint: + + ```bash + python path/to/your_policy_server.py + curl http://localhost:8000/info + ``` + +5. Run a short, single-environment smoke test before launching the full benchmark: + + ```bash + python scripts/evaluation/eval.py --headless \ + --task BallCatching-Franka-DataCollection-v0 \ + --task_profile ball_catching \ + --backend server \ + --server_url http://localhost:8000 \ + --obs_mode vla \ + --control joint_pos \ + --task_description "hold the container with the gripper and catch the thrown ball in the container" \ + --inference_mode async \ + --infer_freq 10 \ + --execution_horizon 8 \ + --num_envs 1 \ + --num_episodes 5 \ + --output outputs/evaluation/smoke_test.json + ``` + +Before a full evaluation, check the following: + +- `--control` must match the policy action representation and the `control_mode` returned by `/info`. See the [action representation table](scripts/evaluation/POLICY_SERVER.md#action-representations) for dimensions and gripper conventions. +- For a vision-language policy, use `--obs_mode vla` and a `DataCollection-v0` task so fixed and wrist cameras are available. The request contains base64-encoded RGB images, proprioception, and `task_description`. +- For a state-only policy, use `--obs_mode state`; `/predict` then receives a flat state batch instead of images. +- The server must preserve the batch dimension and return actions for every requested environment. Begin with `--num_envs 1`, then test the intended parallel batch size. +- Set `--image_history` and `--image_history_stride` to the temporal context expected by the model. Multi-frame camera inputs are ordered from oldest to newest. +- Use `--execution_horizon` to cap how many actions from each returned chunk are executed. It may be shorter than the server's advertised `action_horizon`. +- Add `--use_real_latency` when measuring the effect of actual preprocessing, network transfer, and model inference time. Without it, `--infer_freq` defines a fixed simulated inference period. + +The `--output` JSON contains the full configuration, aggregate success rate, returns, episode lengths, latency/real-time-factor statistics, and per-episode results. Use `--video_dir` when qualitative videos are also needed. + +### Timing and temporal observations + +The simulator, controller, and policy have separate time scales: + +- `--ctrl_freq 25` makes the robot consume one action every 40 ms. +- `--infer_freq 10` defines a fixed policy period of 100 ms. +- `--use_real_latency` replaces the fixed inference period on every request with the measured wall-clock latency converted using the simulator real-time factor. When this flag is present, `--infer_freq` is not the per-cycle delay used for evaluation. +- `--inference_mode sync` applies a freeze-arm latency penalty before executing the newly predicted action chunk. +- `--inference_mode async` executes the previous chunk while a newly predicted chunk is pending. +- `--execution_horizon 8` caps each returned action chunk at eight executable actions. + +For temporal observations, `--image_history T` sends `T` frames per camera, oldest first. `--image_history_stride S` selects every `S`-th captured frame. Thus history 5 with stride 4 spans 17 captured frames including the current frame; at 25 Hz this is nominally 0.64 seconds. History 2 with stride 1 spans two consecutive frames. + +### Reference evaluation commands + +The following commands reproduce the common five-environment, server-based evaluation setup. Each command saves task-specific videos and a JSON result file. + +#### Conveyor Belt Pick-and-Place + +```bash +python scripts/evaluation/eval.py --headless \ + --task ConveyorBeltPickAndPlace-Franka-DataCollection-v0 \ + --backend server \ + --server_url http://localhost:8000 \ + --task_profile conveyor_belt_pick_and_place \ + --inference_mode async --infer_freq 10 \ + --task_description "pick up the cube from the moving conveyor and place it into the bin" \ + --execution_horizon 8 \ + --image_history 5 \ + --image_history_stride 4 \ + --ctrl_freq 25 \ + --num_envs 5 \ + --video_dir eval_videos/conveyor_belt_pick_and_place \ + --num_episodes 150 \ + --use_real_latency \ + --output outputs/evaluation/conveyor_belt_pick_and_place.json +``` + +#### Whack-a-Mole + +```bash +python scripts/evaluation/eval.py --headless \ + --task WhackAMole-Franka-DataCollection-v0 \ + --backend server \ + --server_url http://localhost:8000 \ + --task_profile whack_a_mole \ + --inference_mode async --infer_freq 10 \ + --task_description "hit the mole that pops up on the board with the closed gripper" \ + --execution_horizon 8 \ + --image_history 5 \ + --image_history_stride 4 \ + --ctrl_freq 25 \ + --num_envs 5 \ + --video_dir eval_videos/whack_a_mole \ + --num_episodes 150 \ + --use_real_latency \ + --output outputs/evaluation/whack_a_mole.json +``` + +#### Ball Catching + +```bash +python scripts/evaluation/eval.py --headless \ + --task BallCatching-Franka-DataCollection-v0 \ + --backend server \ + --server_url http://localhost:8000 \ + --task_profile ball_catching \ + --inference_mode async --infer_freq 10 \ + --task_description "hold the container with the gripper and catch the thrown ball in the container" \ + --execution_horizon 8 \ + --image_history 5 \ + --image_history_stride 4 \ + --ctrl_freq 25 \ + --num_envs 5 \ + --video_dir eval_videos/ball_catching \ + --num_episodes 150 \ + --use_real_latency \ + --output outputs/evaluation/ball_catching.json +``` + +#### Rolling Ball Interception + +```bash +python scripts/evaluation/eval.py --headless \ + --task RollingBallInterception-Franka-DataCollection-v0 \ + --backend server \ + --server_url http://localhost:8000 \ + --task_profile rolling_ball_interception \ + --inference_mode async --infer_freq 10 \ + --task_description "catch the ball rolling down the ramp with the container" \ + --execution_horizon 8 \ + --image_history 2 \ + --image_history_stride 1 \ + --ctrl_freq 25 \ + --num_envs 5 \ + --video_dir eval_videos/rolling_ball_interception \ + --num_episodes 150 \ + --use_real_latency \ + --output outputs/evaluation/rolling_ball_interception.json +``` + +#### Ball Throwing + +```bash +python scripts/evaluation/eval.py --headless \ + --task BallThrowing-Franka-DataCollection-v0 \ + --backend server \ + --server_url http://localhost:8000 \ + --task_profile ball_throwing \ + --inference_mode async --infer_freq 10 \ + --task_description "throw the ball into the bin" \ + --execution_horizon 8 \ + --image_history 5 \ + --image_history_stride 4 \ + --ctrl_freq 25 \ + --num_envs 5 \ + --video_dir eval_videos/ball_throwing \ + --num_episodes 150 \ + --use_real_latency \ + --output outputs/evaluation/ball_throwing.json +``` + +#### Rotating Peg Insertion + +```bash +python scripts/evaluation/eval.py --headless \ + --task RotatingPegInsertion-Franka-DataCollection-v0 \ + --backend server \ + --server_url http://localhost:8000 \ + --task_profile rotating_peg_insertion \ + --inference_mode async --infer_freq 10 \ + --task_description "insert the peg into the hole on the rotating disc" \ + --execution_horizon 8 \ + --image_history 5 \ + --image_history_stride 4 \ + --ctrl_freq 25 \ + --num_envs 5 \ + --video_dir eval_videos/rotating_peg_insertion \ + --num_episodes 150 \ + --use_real_latency \ + --output outputs/evaluation/rotating_peg_insertion.json +``` + + +## Citation + +If ReflexBench is useful in your research, please cite: + +```bibtex +@article{chen2026reflex, + title = {Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation}, + author = {Chen, Yuxuan and Zhang, Wanruo and Li, Xiao}, + journal = {arXiv preprint arXiv:2608.14379}, + year = {2026} +} +``` + +## License + +This project is released under the [BSD 3-Clause License](LICENSE). Individual files retain their original copyright notices. diff --git a/reference/scripts/data_collection/task_prompts.py b/reference/scripts/data_collection/task_prompts.py new file mode 100644 index 0000000000000000000000000000000000000000..97588bcdce08438f2a1d001c2eaedc1934401013 --- /dev/null +++ b/reference/scripts/data_collection/task_prompts.py @@ -0,0 +1,118 @@ +# Copyright (c) 2022-2025, The Isaac Lab Project Developers. +# All rights reserved. +# SPDX-License-Identifier: BSD-3-Clause + +"""Per-task language prompts for VLA data collection / LeRobot conversion. + +Keyed by the task slug produced by :func:`_task_slug` in both +``collect_vla_data.py`` and ``convert_to_lerobot.py``. Accessed via +:func:`resolve_prompt_from_task`, which normalizes any Gym id (e.g. +``ConveyorBeltPickAndPlace-Franka-DataCollection-v0``) into the same slug. + +Keep the wording short, action-driven, and English-only; VLA tokenizers +handle these best. If a slug is missing, we fall back to +``LEGACY_DEFAULT_PROMPT`` so both scripts degrade gracefully. +""" + +from __future__ import annotations + +# Legacy default used as both the argparse default in collect_vla_data.py +# and the sentinel for "user did not customize the prompt" when deciding +# whether to auto-fill from the task lookup. +LEGACY_DEFAULT_PROMPT: str = "manipulate the object" + + +# +# Keys match the slug produced by ``_task_slug`` in ``collect_vla_data.py`` +# and ``convert_to_lerobot.py`` (suffixes + robot tokens stripped, then joined +# by underscore). We also register the "spelled-out" variant (e.g. +# ``conveyor_belt_pick_and_place``) as a synonym for humans who call the resolver +# directly with task profile names. +_CONVEYOR_BELT_PICK_AND_PLACE = ( + "pick up the cube from the moving conveyor and place it into the bin" +) +_WHACK_A_MOLE = "hit the mole that pops up on the board with the closed gripper" +_BALL_CATCHING = ( + "hold the container with the gripper and catch the thrown ball in the container" +) +_ROLLING_BALL_INTERCEPTION = "catch the ball rolling down the ramp with the container" +_ROTATING_PEG_INSERTION = "insert the peg into the hole on the rotating disc" +_BALL_THROWING = "throw the ball into the bin" + +TASK_PROMPTS: dict[str, str] = { + # slug as produced by `_task_slug(gym_id)`: + "conveyorbeltpickandplace": _CONVEYOR_BELT_PICK_AND_PLACE, + "whackamole": _WHACK_A_MOLE, + "ballcatching": _BALL_CATCHING, + "rollingballinterception": _ROLLING_BALL_INTERCEPTION, + "rotatingpeginsertion": _ROTATING_PEG_INSERTION, + "ballthrowing": _BALL_THROWING, + # human-readable profile names (also accepted): + "conveyor_belt_pick_and_place": _CONVEYOR_BELT_PICK_AND_PLACE, + "whack_a_mole": _WHACK_A_MOLE, + "ball_catching": _BALL_CATCHING, + "rolling_ball_interception": _ROLLING_BALL_INTERCEPTION, + "rotating_peg_insertion": _ROTATING_PEG_INSERTION, + "ball_throwing": _BALL_THROWING, +} + + +def _slugify(task_name: str) -> str: + """Normalize a task/gym id into a lookup slug. + + Mirrors ``_task_slug`` in ``collect_vla_data.py`` / ``convert_to_lerobot.py``: + strips known suffixes and robot tokens, then joins with underscores. + Also accepts already-slugified inputs like ``conveyor_belt_pick_and_place``. + """ + if not task_name: + return "" + normalized = task_name.lower().strip() + + # Already a slug (no dashes) -> just return as-is (after normalizing underscores). + if "-" not in normalized and "_" in normalized: + return normalized + + for suffix in ("-datacollection-v0", "-play-v0", "-ik-abs-v0", "-ik-rel-v0", "-v0"): + if normalized.endswith(suffix): + normalized = normalized[: -len(suffix)] + break + + tokens = [ + token for token in normalized.split("-") + if token and token not in {"franka", "panda", "ur5", "ur10", "xarm", "kinova"} + ] + if not tokens: + return normalized.replace("-", "_") + return "_".join(tokens) + + +def resolve_prompt_from_task( + task_name: str | None, + default: str = LEGACY_DEFAULT_PROMPT, +) -> str: + """Return the prompt registered for *task_name*, else *default*.""" + if not task_name: + return default + slug = _slugify(task_name) + return TASK_PROMPTS.get(slug, default) + + +def resolve_prompt( + task_name: str | None, + user_prompt: str | None, + legacy_default: str = LEGACY_DEFAULT_PROMPT, +) -> str: + """Decide which prompt to use. + + Priority: + 1. Non-empty *user_prompt* that differs from the legacy default. + 2. Task-specific prompt from :data:`TASK_PROMPTS`. + 3. *legacy_default*. + + This means the user can still override via ``--prompt "my custom text"``, + while leaving ``--prompt`` untouched (or equal to the legacy default) + triggers per-task auto-fill. + """ + if user_prompt is not None and user_prompt != "" and user_prompt != legacy_default: + return user_prompt + return resolve_prompt_from_task(task_name, default=legacy_default) diff --git a/reference/scripts/evaluation/task_profiles.py b/reference/scripts/evaluation/task_profiles.py new file mode 100644 index 0000000000000000000000000000000000000000..f120266c663fdb37432922bffedc750365899aa6 --- /dev/null +++ b/reference/scripts/evaluation/task_profiles.py @@ -0,0 +1,270 @@ +"""Task-specific profiles for evaluation. + +Each profile contains: +- gym_id: Registered Gym environment name (uses DataCollection-v0 so that + evaluation shares exactly the same scene, cameras and reset events as the + data-collection pipeline, including the ``mark_wrist_cam_usd_dirty`` Fabric + workaround) +- action_scale: Scaling factor for arm joint-relative actions +- success_type: How to determine episode success +- phase_names: Human-readable names for task phases (diagnostics) +- has_ik_override: Whether to disable env's built-in IK override +- WhackAMole-specific popup timing overrides +- ConveyorBeltPickAndPlace box ranges for object_in_box check + +Helper functions: +- check_success(): Evaluate success for a given task profile +- apply_whack_a_mole_eval_overrides(): Override popup timing for eval +- install_phase_tracker(): Patch _reset_idx to capture phase at termination +""" + +from __future__ import annotations + +import torch + + +# ============================================================ +# Task Profiles Registry +# ============================================================ + +TASK_PROFILES: dict[str, dict] = { + "conveyor_belt_pick_and_place": { + "gym_id": "ConveyorBeltPickAndPlace-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": True, + "short_circuit_success": True, + "success_type": "object_in_box", + "phase_names": { + 0: "approach", 1: "lift", 2: "transport", 3: "release", 4: "return", 5: "done", + }, + "box_x_range": (-0.2, 0.2), + "box_y_range": (-0.6, -0.3), + "box_z_range": (0.0, 0.08), + }, + "ball_catching": { + "gym_id": "BallCatching-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": False, + "short_circuit_success": True, + "success_type": "task_phase_4", + "phase_names": { + 0: "wait", 1: "launch", 2: "predict", 3: "position", 4: "catch", + }, + }, + "rolling_ball_interception": { + "gym_id": "RollingBallInterception-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": False, + "short_circuit_success": True, + "success_type": "task_phase_4", + "phase_names": { + 0: "wait", 1: "roll", 2: "predict", 3: "position", 4: "catch", + }, + }, + "whack_a_mole": { + "gym_id": "WhackAMole-Franka-DataCollection-v0", + "action_scale": 0.2, + "has_ik_override": False, + "short_circuit_success": False, + "success_type": "whack_a_mole", + "popup_duration_s": 2.0, + "popup_gap_s": 0.3, + "popup_initial_delay_s": 0.0, + "eval_episode_length_s": 3.0, + "phase_names": { + 0: "wait popup", 1: "move", 2: "strike", 3: "return", 4: "done", + }, + }, + "ball_throwing": { + "gym_id": "BallThrowing-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": False, + "short_circuit_success": True, + "success_type": "task_phase_2", + "phase_names": { + 0: "swing", 1: "release", 2: "in box", + }, + }, + "rotating_peg_insertion": { + "gym_id": "RotatingPegInsertion-Franka-DataCollection-v0", + "action_scale": 0.1, + "has_ik_override": False, + "short_circuit_success": True, + "success_type": "task_phase_4", + "phase_names": { + 0: "pre-align", 1: "track", 2: "wait alignment", 3: "insert", 4: "done", + }, + }, +} + + +def resolve_profile(name_or_gym_id: str) -> dict | None: + """Look up a profile by short name or gym_id. Returns None if not found.""" + if name_or_gym_id in TASK_PROFILES: + return TASK_PROFILES[name_or_gym_id] + for profile in TASK_PROFILES.values(): + if profile["gym_id"] == name_or_gym_id: + return profile + return None + + +# ============================================================ +# Success Checking +# ============================================================ + +def check_success(manager_env, task_profile: dict, env_id: int = 0) -> bool: + """Evaluate success for a single env according to the task profile.""" + st = task_profile["success_type"] + if st == "object_in_box": + obj = manager_env.scene["object"] + local = ( + obj.data.root_pos_w[env_id, :3] + - manager_env.scene.env_origins[env_id, :3] + ) + bx = task_profile["box_x_range"] + by = task_profile["box_y_range"] + bz = task_profile["box_z_range"] + return bool( + bx[0] <= local[0].item() <= bx[1] + and by[0] <= local[1].item() <= by[1] + and bz[0] <= local[2].item() <= bz[1] + ) + elif st == "task_phase_4": + return ( + hasattr(manager_env, "task_phase") + and manager_env.task_phase[env_id].item() == 4 + ) + elif st == "task_phase_2": + return ( + hasattr(manager_env, "task_phase") + and manager_env.task_phase[env_id].item() == 2 + ) + elif st == "whack_a_mole": + return ( + hasattr(manager_env, "valid_hits") + and manager_env.valid_hits[env_id].item() > 0 + ) + return False + + +# ============================================================ +# WhackAMole Eval Overrides +# ============================================================ + +def apply_whack_a_mole_eval_overrides(manager_env, task_profile: dict | None) -> None: + """Override popup timing for WhackAMole evaluation.""" + if not task_profile or task_profile.get("success_type") != "whack_a_mole": + return + if not hasattr(manager_env, "popup_durations") or not hasattr( + manager_env, "popup_start_times" + ): + return + + popup_duration_s = float(task_profile.get("popup_duration_s", 1.0)) + popup_gap_s = float(task_profile.get("popup_gap_s", 0.3)) + popup_initial_delay_s = float(task_profile.get("popup_initial_delay_s", 1.0)) + + manager_env.popup_durations.fill_(popup_duration_s) + start_times = torch.zeros_like(manager_env.popup_start_times) + start_times[:, 0] = popup_initial_delay_s + for i in range(1, start_times.shape[1]): + start_times[:, i] = start_times[:, i - 1] + popup_duration_s + popup_gap_s + manager_env.popup_start_times.copy_(start_times) + + +# ============================================================ +# Phase Tracker +# ============================================================ + +def install_phase_tracker(manager_env) -> bool: + """Patch _reset_idx to capture task_phase at termination time.""" + manager_env._phase_at_term = -1 + if not hasattr(manager_env, "_reset_idx"): + print(" [WARN] _reset_idx not found - phase_at_term unavailable") + return False + original_reset_idx = manager_env._reset_idx + + def _patched_reset_idx(env_ids, *args, **kwargs): + if len(env_ids) > 0 and hasattr(manager_env, "task_phase"): + manager_env._phase_at_term = manager_env.task_phase[env_ids[0]].item() + return original_reset_idx(env_ids, *args, **kwargs) + + manager_env._reset_idx = _patched_reset_idx + print(" Phase tracker installed") + return True + + +# ============================================================ +# WhackAMole Debug Diagnostics +# ============================================================ + +def debug_whack_a_mole_press(manager_env, step_idx: int, env_id: int = 0) -> None: + """Print press-detection diagnostics for WhackAMole.""" + if not hasattr(manager_env, "window_active"): + return + if not manager_env.window_active[env_id]: + return + + from isaaclab.sensors import FrameTransformer + + robot = manager_env.scene["robot"] + ee_frame: FrameTransformer = manager_env.scene["ee_frame"] + ee_pos_w = ee_frame.data.target_pos_w[env_id, 0, :] + ee_pos_local = ee_pos_w - manager_env.scene.env_origins[env_id] + + active_mid = int(manager_env.active_mole_id[env_id].item()) + if active_mid < 0: + return + + mole_xy = manager_env.mole_positions_local[env_id, active_mid, :2] + mole_z = manager_env.mole_heights[env_id, active_mid].item() + + xy_dist = torch.norm(ee_pos_local[:2] - mole_xy).item() + ee_z = ee_pos_local[2].item() + + finger_ids = robot.find_joints(["panda_finger.*"])[0] + finger_pos = robot.data.joint_pos[env_id, finger_ids] + finger_width = finger_pos.sum().item() + + BOARD_SURFACE_Z = 0.22 + XY_THR = 0.035 + Z_MAX = BOARD_SURFACE_Z + 0.018 + Z_MIN = BOARD_SURFACE_Z - 0.010 + GRIP_THR = 0.03 + + ok_xy = xy_dist < XY_THR + ok_z = Z_MIN < ee_z < Z_MAX + ok_grip = finger_width < GRIP_THR + dwell = manager_env.press_dwell_counter[env_id].item() + hit_reg = manager_env.window_hit_registered[env_id].item() + valid_hits = manager_env.valid_hits[env_id].item() + win_idx = manager_env.current_window_idx[env_id].item() + timer = manager_env.episode_timer[env_id].item() + + print( + f" [WAM-DBG] step={step_idx:>4} t={timer:.2f}s win={win_idx} mole={active_mid} " + f"| ee_xy=({ee_pos_local[0].item():.4f},{ee_pos_local[1].item():.4f}) " + f"mole_xy=({mole_xy[0].item():.4f},{mole_xy[1].item():.4f}) " + f"xy_d={xy_dist:.4f} {'OK' if ok_xy else 'FAR':>3} " + f"| ee_z={ee_z:.4f} [{Z_MIN:.3f},{Z_MAX:.3f}] " + f"{'OK' if ok_z else ('HI' if ee_z >= Z_MAX else 'LO'):>2} " + f"| grip_w={finger_width:.4f} {'CLOSED' if ok_grip else 'OPEN':>6} " + f"| dwell={dwell} hit={hit_reg} total_hits={valid_hits}" + ) + + +# ============================================================ +# Smoothness Metrics +# ============================================================ + +def calculate_smoothness(actions_list: list) -> tuple[float, float]: + """Compute (avg_diff, avg_jerk) from a list of action arrays.""" + import numpy as np + + if len(actions_list) < 3: + return 0.0, 0.0 + actions = np.array(actions_list) + arm_actions = actions[:, :7] if actions.shape[-1] >= 7 else actions + diff1 = np.linalg.norm(np.diff(arm_actions, axis=0), axis=1) + diff2 = np.linalg.norm(np.diff(arm_actions, n=2, axis=0), axis=1) + return float(np.mean(diff1)), float(np.mean(diff2)) diff --git a/reference/source/reflexbench/reflexbench/tasks/manager_based/ball_catching/README.md b/reference/source/reflexbench/reflexbench/tasks/manager_based/ball_catching/README.md new file mode 100644 index 0000000000000000000000000000000000000000..36d8989d2c5e708087f41a4ee681acc9ad1370e7 --- /dev/null +++ b/reference/source/reflexbench/reflexbench/tasks/manager_based/ball_catching/README.md @@ -0,0 +1,57 @@ +# Ball Catching (Franka) + +Catch a launched ball with the Franka end-effector acting as a virtual bucket. Supports joint position control and IK (absolute/relative) control. + +## Registered tasks + +| Task | Description | +|------|-------------| +| `BallCatching-Franka-v0` | Joint position control (7-DOF + gripper) | +| `BallCatching-Franka-Play-v0` | Same, play/eval variant (fewer envs, no obs noise) | +| `BallCatching-Franka-IK-Abs-v0` | IK absolute pose control | +| `BallCatching-Franka-IK-Rel-v0` | IK relative pose control | +| `BallCatching-Franka-DataCollection-v0` | Same task with fixed + wrist cameras for VLA data collection | + +## Task phases and success + +The task uses a phased state machine (`task_phase` in `mdp/events.py`): + +| Phase | Name | Description | +|-------|------|-------------| +| 0 | Wait | Ball is reset at the launcher and waiting for launch | +| 1 | Launch detected | Ball has been launched and motion tracking begins | +| 2 | Intercept | A ballistic intercept point has been predicted | +| 3 | Catch | EE is near the intercept point and waiting to contain the ball | +| 4 | Done | Ball stays in the catch zone for the hold threshold | + +**Success (episode termination):** +Defined by **phase 4**. The ball must remain inside the virtual catch zone below the end-effector for consecutive steps. + +## Data collection + +From the repo root: + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task BallCatching-Franka-DataCollection-v0 \ + --policy checkpoint \ + --control joint_pos \ + --num_episodes 200 +``` + +- **`--control`**: Must match the policy (`joint_pos`, `ik_abs`, `ik_rel`). +- **`--fps`**: Robot control frequency and dataset FPS (Hz). Default: task config (25 Hz). + +## Evaluation + +```bash +python scripts/evaluation/eval.py \ + --task BallCatching-Franka-DataCollection-v0 \ + --server_url http://localhost:8000 \ + --control joint_pos \ + --inference_mode async --infer_freq 10 \ + --num_episodes 50 --output results.json +``` + +- **`--control`**: Must match the policy. +- **`--infer_freq`**: Inference frequency in Hz (e.g. 10 = one chunk every 100 ms); internally converted to physics sub-steps. diff --git a/reference/source/reflexbench/reflexbench/tasks/manager_based/ball_throwing/README.md b/reference/source/reflexbench/reflexbench/tasks/manager_based/ball_throwing/README.md new file mode 100644 index 0000000000000000000000000000000000000000..8ff3ba5a384bf4f8fb24562db739d5082427b960 --- /dev/null +++ b/reference/source/reflexbench/reflexbench/tasks/manager_based/ball_throwing/README.md @@ -0,0 +1,87 @@ +# Ball Throwing (Franka) + +Throw a small ball, **already grasped by the gripper at episode start**, into a +target box placed directly in front of the robot. The ball is initialised +between the two fingers; the policy only needs to swing the arm and open the +gripper at the right moment. + +## Registered tasks + +| Task | Description | +|------|-------------| +| `BallThrowing-Franka-v0` | Joint position control (7-DOF + gripper) | +| `BallThrowing-Franka-Play-v0` | Same, play/eval variant (50 envs, no obs noise) | +| `BallThrowing-Franka-IK-Abs-v0` | IK absolute pose control | +| `BallThrowing-Franka-IK-Rel-v0` | IK relative pose control | +| `BallThrowing-Franka-DataCollection-v0` | Same task with fixed + wrist cameras | + +## Scene + +- **Robot**: Franka Panda (`FRANKA_PANDA_HIGH_PD_CFG`), default arm joint + pose. Finger joints are initialised closed (≈0.026 m half-aperture) so the + gripper is already clamped on the ball. +- **Ball**: blue solid sphere, radius 0.025 m, mass 0.04 kg. Spawned at the + EE frame target minus 2.2 cm along its -Z (between the two fingers) by + `reset_ball_in_gripper`. Gravity is **disabled at spawn** so the ball + cannot drop before the gripper command stabilises; an interval event + (`apply_post_release_gravity`) re-applies `mass * g` as an external force + once the task transitions to phase 1. +- **Box**: Isaac KLT bin (`Props/KLT_Bin/small_KLT_visual_collision.usd`) at + `[0.8, 0.0, 0.075]` (0.8 m in front of the robot along +X, well past the + Franka workspace edge -- only reachable via a real throw). The bin is + oriented so its long edge (~0.30 m) lies along +X (the throw direction), + giving a more forgiving catch window for X-axis landing error. A startup + event applies convex decomposition so the bin's opening is not sealed by + a single convex hull. + +## Task phases and success + +Phase machine (`task_phase` in `mdp/events.py::check_phase_transitions`): + +| Phase | Name | Description | +|-------|------|-------------| +| 0 | Hold | Ball in gripper, robot is swinging the arm | +| 1 | Released | Gripper opened (finger width ≥ 0.06 m) or ball drifted > 0.08 m from EE | +| 2 | Done | Ball inside target box volume (success) | + +**Success:** `task_phase == 2`. Object-in-box uses env-local bounds +`|x − cx| ≤ 0.13, |y − cy| ≤ 0.09, z ∈ [0.02, 0.18]` (rectangular catch +volume aligned with the bin's long edge) where `(cx, cy, cz)` is the +randomised env-local box centre (jittered ±5 cm in XY at every reset). +See `object_in_box()` in `mdp/terminations.py`. + +**Failure:** time-out (`episode_length_s = 4 s`) or ball drops below +z = -0.05 m (missed the box and rolled off the floor). + +## Quick smoke test + +```bash +python3 -c " +import gymnasium as gym +import reflexbench.tasks.manager_based.ball_throwing # registers Gym IDs +print(gym.spec('BallThrowing-Franka-Play-v0')) +" +``` + +## Data collection + +```bash +python3 scripts/data_collection/collect_vla_data.py \ + --task BallThrowing-Franka-DataCollection-v0 \ + --policy planning \ + --control joint_pos \ + --num_episodes 200 +``` + +## Evaluation + +Use the matching task ID and control representation for evaluation. + +```bash +python3 scripts/evaluation/eval.py \ + --task BallThrowing-Franka-DataCollection-v0 \ + --server_url http://localhost:8000 \ + --control joint_pos \ + --inference_mode async --ctrl_freq 10 \ + --num_episodes 50 --output results.json +``` diff --git a/reference/source/reflexbench/reflexbench/tasks/manager_based/conveyor_belt_pick_and_place/README.md b/reference/source/reflexbench/reflexbench/tasks/manager_based/conveyor_belt_pick_and_place/README.md new file mode 100644 index 0000000000000000000000000000000000000000..427604e740eb35531432f23915d81539399d4d98 --- /dev/null +++ b/reference/source/reflexbench/reflexbench/tasks/manager_based/conveyor_belt_pick_and_place/README.md @@ -0,0 +1,77 @@ +# Conveyor Belt Pick-and-Place (Franka) + +Pick object from a moving conveyor belt and place it into a box. Supports joint position control and IK (absolute/relative) control. + +## Registered tasks + +| Task | Description | +|------|-------------| +| `ConveyorBeltPickAndPlace-Franka-v0` | Joint position control (7-DOF + gripper) | +| `ConveyorBeltPickAndPlace-Franka-Play-v0` | Same, play/eval variant (fewer envs, no obs noise) | +| `ConveyorBeltPickAndPlace-Franka-IK-Abs-v0` | IK absolute pose control | +| `ConveyorBeltPickAndPlace-Franka-IK-Rel-v0` | IK relative pose control | +| `ConveyorBeltPickAndPlace-Franka-DataCollection-v0` | Same task with fixed + wrist cameras for VLA data collection | + + +## Task phases and success + +The task uses a phased state machine (`task_phase` in `mdp/events.py`): + +| Phase | Name | Description | +|-------|------|-------------| +| 0 | Approach | Move EE toward the object on the conveyor | +| 1 | Grasp | EE close to object; close gripper and lift | +| 2 | Transport | Object above lift height (0.25 m); IK moves arm toward box target | +| 3 | Release | Arm at box; delayed gripper open to drop object | +| 4 | Done | Object detected inside box | + +**Success (episode termination):** +Defined by **object in box** (env-local coords: x ∈ [−0.2, 0.2], y ∈ [−0.6, −0.3], z ∈ [0.0, 0.08]). `task_completed` uses `object_in_box()` — the same thresholds in events.py, rewards.py, and terminations.py. + +## RL training and data collection + +Conveyor Belt Pick-and-Place currently requires a trained RL policy for demonstration collection. Unlike the other five ReflexBench tasks, it does not support the built-in planning policy. + +Train an skrl checkpoint from the repository root: + +```bash +python scripts/skrl/train.py \ + --task ConveyorBeltPickAndPlace-Franka-v0 \ + --headless +``` + +Collect demonstrations using the resulting checkpoint: + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task ConveyorBeltPickAndPlace-Franka-DataCollection-v0 \ + --policy checkpoint \ + --checkpoint /path/to/conveyor_policy.pt \ + --control joint_pos \ + --num_envs 5 \ + --num_episodes 200 +``` + +- **`--checkpoint`**: Must point to a trained skrl `.pt` checkpoint. +- **`--control`**: Must match the policy (`joint_pos`, `ik_abs`, `ik_rel`). Sets action and state format. +- **`--fps`**: Robot control frequency and dataset FPS (Hz). Default: task config (25 Hz). +- **`--policy planning`**: Not supported for this task. + +Output: HDF5 under `scripts/data_collection/collected_data/` (or `--output`). + +## Evaluation + +Policy served by a remote server (see `scripts/evaluation/POLICY_SERVER.md`): + +```bash +python scripts/evaluation/eval.py \ + --task ConveyorBeltPickAndPlace-Franka-DataCollection-v0 \ + --server_url http://localhost:8000 \ + --control joint_pos \ + --inference_mode async --infer_freq 10 \ + --num_episodes 50 --output results.json +``` + +- **`--control`**: Must match the policy (use `--state_format auto` so state follows control). +- **`--infer_freq`**: Inference frequency in Hz (e.g. 10 = one chunk every 100 ms); internally converted to physics sub-steps (see main README Time model). +- **`--ctrl_freq`**: Override robot control frequency (Hz). diff --git a/reference/source/reflexbench/reflexbench/tasks/manager_based/rolling_ball_interception/README.md b/reference/source/reflexbench/reflexbench/tasks/manager_based/rolling_ball_interception/README.md new file mode 100644 index 0000000000000000000000000000000000000000..bfc8c5608345b013e8dff0d4fc96364ece98ae3d --- /dev/null +++ b/reference/source/reflexbench/reflexbench/tasks/manager_based/rolling_ball_interception/README.md @@ -0,0 +1,35 @@ +# Rolling Ball Interception (Franka) + +Intercept a ball rolling down a ramp using a virtual catcher attached to the Franka end-effector. Supports joint position control and IK (absolute/relative) control. + +## Registered tasks + +| Task | Description | +|------|-------------| +| `RollingBallInterception-Franka-v0` | Joint position control (7-DOF + gripper) | +| `RollingBallInterception-Franka-Play-v0` | Same, play/eval variant (fewer envs, no obs noise) | +| `RollingBallInterception-Franka-IK-Abs-v0` | IK absolute pose control | +| `RollingBallInterception-Franka-IK-Rel-v0` | IK relative pose control | +| `RollingBallInterception-Franka-DataCollection-v0` | Same task with fixed + wrist cameras for VLA data collection | + +## Task phases and success + +The task uses a phased state machine (`task_phase` in `mdp/events.py`): + +| Phase | Name | Description | +|-------|------|-------------| +| 0 | Wait | Ball on ramp, gate closed, random delay counting down | +| 1 | Rolling | Gate opened, ball rolling down the ramp | +| 2 | Intercept | (placeholder) Move catcher to ramp exit point | +| 3 | Capture | (placeholder) Hold catcher at exit, absorb ball | +| 4 | Done | Ball retained in catcher for hold threshold | + +**Success (episode termination):** +Defined by **phase 4**. The ball must remain inside the virtual catch zone below the end-effector for consecutive steps. + +## Scene layout + +- **Ramp**: 0.30 m long, 0.10 m wide, tilted 20°, with guide rails on both sides +- **Ball**: Sphere (r=0.038 m, m=0.10 kg) placed at the top of the ramp +- **Catcher**: Cylinder (r=0.06 m, h=0.10 m) teleported to follow end-effector +- **Gate**: Ball is held stationary for a random delay (0.3–0.8 s), then released to roll under gravity diff --git a/reference/source/reflexbench/reflexbench/tasks/manager_based/rotating_peg_insertion/README.md b/reference/source/reflexbench/reflexbench/tasks/manager_based/rotating_peg_insertion/README.md new file mode 100644 index 0000000000000000000000000000000000000000..791315186b5dad421968d176e65392b05fa105b7 --- /dev/null +++ b/reference/source/reflexbench/reflexbench/tasks/manager_based/rotating_peg_insertion/README.md @@ -0,0 +1,35 @@ +# Rotating Peg Insertion (Franka) + +Insert a pre-grasped peg into a hole on a continuously rotating disc. The robot must synchronize with periodic alignment windows to perform timed insertion. + +## Registered tasks + +| Task | Description | +|------|-------------| +| `RotatingPegInsertion-Franka-v0` | Joint position control (7-DOF + gripper) | +| `RotatingPegInsertion-Franka-Play-v0` | Same, play/eval variant (fewer envs, no obs noise) | +| `RotatingPegInsertion-Franka-IK-Abs-v0` | IK absolute pose control | +| `RotatingPegInsertion-Franka-IK-Rel-v0` | IK relative pose control | +| `RotatingPegInsertion-Franka-DataCollection-v0` | Same task with fixed + wrist cameras for VLA data collection | + +## Task phases + +| Phase | Name | Description | +|-------|------|-------------| +| 0 | Pre-align | Robot moves toward hover position above disc | +| 1 | Track disc | Monitoring disc rotation and predicting alignment windows | +| 2 | Wait for window | Alignment window predicted, waiting for lead time | +| 3 | Descend / Insert | Timed descent into hole during alignment window | +| 4 | Done | Peg held in hole for required duration | + +## Scene layout + +- Franka Panda at origin +- Rotating disc at (0.5, 0.0, 0.40) on a pedestal +- Disc: radius 0.14 m, 1 hole (diameter 0.10 m), angular velocity 20-60 deg/s +- Peg: radius 0.005 m, length 0.10 m, pre-grasped (follows EE) +- Green marker on disc surface indicates hole position + +## Success condition + +Peg tip enters hole within radius tolerance AND descends >= 0.02 m below disc surface AND holds for >= 5 control steps. diff --git a/reference/source/reflexbench/reflexbench/tasks/manager_based/whack_a_mole/README.md b/reference/source/reflexbench/reflexbench/tasks/manager_based/whack_a_mole/README.md new file mode 100644 index 0000000000000000000000000000000000000000..54cb108af12314000f0df6ae19e8a0102be8b5f3 --- /dev/null +++ b/reference/source/reflexbench/reflexbench/tasks/manager_based/whack_a_mole/README.md @@ -0,0 +1,52 @@ +# Whack-a-Mole (Franka) + +Reactive striking task: moles pop up on a board on a fixed schedule; the robot must press the active mole with a **closed** gripper within each time window. Supports joint position control and IK (absolute/relative) control. + +## Registered tasks + +| Task | Description | +|------|-------------| +| `WhackAMole-Franka-v0` | Joint position control (7-DOF + gripper) | +| `WhackAMole-Franka-Play-v0` | Same, play/eval variant (fewer envs, no obs noise) | +| `WhackAMole-Franka-IK-Abs-v0` | IK absolute pose control | +| `WhackAMole-Franka-IK-Rel-v0` | IK relative pose control | +| `WhackAMole-Franka-DataCollection-v0` | Same task with fixed + wrist cameras for VLA data collection | + +## Mechanics and success + +- **Board**: Five moles in a fixed XY layout (`mdp/events.py`). Each episode samples a schedule of **8** popup windows; each window activates one mole for a duration (defaults in env cfg; eval profile `whack_a_mole` can override timing via `scripts/evaluation/task_profiles.py`). +- **Press detection**: End-effector must be within XY/Z thresholds over the active mole, gripper sufficiently closed, and hold for a short dwell (`PRESS_DWELL_STEPS` in `mdp/events.py`). Valid strikes increment `valid_hits`. +- **Episode termination**: Internal `task_phase` moves from **0** (windows in progress) to **4** after all windows have been processed (hit or missed). Training rewards use hit rate; unified eval profile success is **`valid_hits > 0`** (see `check_success` in `task_profiles.py`). + +Diagnostics: run `scripts/evaluation/eval.py` with `--debug_whack` for per-step press-detection prints. + +## Data collection + +From the repo root: + +```bash +python scripts/data_collection/collect_vla_data.py \ + --task WhackAMole-Franka-DataCollection-v0 \ + --policy checkpoint \ + --control joint_pos \ + --num_envs 1 \ + --num_episodes 100 +``` + +- **`--control`**: Must match the policy (`joint_pos`, `ik_abs`, `ik_rel`). +- **`--fps`**: Robot control frequency and dataset FPS (Hz). Default follows task config. + +## Evaluation + +```bash +python scripts/evaluation/eval.py \ + --task WhackAMole-Franka-DataCollection-v0 \ + --task_profile whack_a_mole \ + --server_url http://localhost:8000 \ + --control joint_pos \ + --inference_mode async --infer_freq 10 \ + --num_episodes 50 --output results.json +``` + +- **`--task_profile whack_a_mole`**: Applies eval-specific popup timing and success logic when needed. +- **`--infer_freq`**: Inference frequency in Hz; internally converted to physics sub-steps. diff --git a/scripts/build_examples.py b/scripts/build_examples.py new file mode 100644 index 0000000000000000000000000000000000000000..da67591217d3714311c1e0daf9db5288063ef615 --- /dev/null +++ b/scripts/build_examples.py @@ -0,0 +1,268 @@ +"""Selective official benchmark examples. Run: prepare, download, render, package, publish. +The same implementation supports ReflexBench and DynamicVLA using the workspace name. +""" +from pathlib import Path +import ast, collections, concurrent.futures as cf, hashlib, io, json, math, shutil, subprocess, sys, time +from fractions import Fraction +import requests +from requests.adapters import HTTPAdapter +from urllib3.util.retry import Retry +import pyarrow as pa +import pyarrow.parquet as pq + +ROOT=Path(__file__).resolve().parents[1] +NAME=ROOT.name +REFLEX=NAME=='ReflexBench' +REPO='cyx337/ReflexBench_dataset' if REFLEX else 'hzxie/DOM' +DEST=f'Travor278/{NAME}-Task-Examples' +WORK=ROOT/'work';OUT=ROOT/'dataset' +CODE=WORK/'official-code' +GITHUB='LxRoboticsLab/ReflexBench' if REFLEX else 'hzxie/DynamicVLA' +SESSION=requests.Session() +SESSION.mount('https://',HTTPAdapter(max_retries=Retry(total=4,backoff_factor=.6,status_forcelist=[429,500,502,503,504]))) + +def read(p):return json.loads(p.read_text(encoding='utf-8')) +def write(p,x):p.parent.mkdir(parents=True,exist_ok=True);p.write_text(json.dumps(x,indent=2,ensure_ascii=False),encoding='utf-8') +def url(p):return f'https://huggingface.co/datasets/{REPO}/resolve/{SOURCE_REV}/{p}' +def download_file(p,dst): + if dst.exists():return + dst.parent.mkdir(parents=True,exist_ok=True) + with SESSION.get(url(p),stream=True,timeout=(20,120)) as r: + r.raise_for_status() + with dst.with_suffix(dst.suffix+'.part').open('wb') as f: + for b in r.iter_content(1024*1024):f.write(b) + dst.with_suffix(dst.suffix+'.part').replace(dst) + +class RangeReader(io.RawIOBase): + """Seekable HTTP range reader: no full video-shard download or hidden HF cache.""" + def __init__(self,path,size,block=262144): + self.path=path;self.size=size;self.block=block;self.pos=0;self.cache=collections.OrderedDict();self.transferred=0 + def readable(self):return True + def seekable(self):return True + def tell(self):return self.pos + def seek(self,offset,whence=0): + self.pos=offset if whence==0 else self.pos+offset if whence==1 else self.size+offset + if self.pos<0:raise ValueError('negative seek') + return self.pos + def read(self,n=-1): + if n<0:n=self.size-self.pos + n=min(n,self.size-self.pos);out=[] + while n>0: + index=self.pos//self.block + if index not in self.cache: + start=index*self.block;end=min(start+self.block,self.size)-1 + r=SESSION.get(url(self.path),headers={'Range':f'bytes={start}-{end}'},timeout=(20,90));r.raise_for_status() + if r.status_code!=206 or not r.headers.get('Content-Range','').startswith(f'bytes {start}-'): + raise ValueError('Source did not honor bounded HTTP range') + self.cache[index]=r.content;self.transferred+=len(r.content) + if len(self.cache)>24:self.cache.popitem(last=False) + b=self.cache[index];offset=self.pos%self.block;amount=min(n,len(b)-offset) + if amount<=0:raise EOFError('truncated HTTP range') + out.append(b[offset:offset+amount]);self.pos+=amount;n-=amount + return b''.join(out) + +def lookup_jsonl(path,target,field,size): + """Locate a sorted metadata record using small byte ranges, retaining only matched rows.""" + low=0;high=size;low_id=0;high_id=(207306 if field=='episode_index' else 140932) + for attempt in range(22): + guess=int(low+(high-low)*max(0,min(1,(target-low_id)/max(1,high_id-low_id)))) + start=max(0,min(size-131072,guess-32768));end=min(size-1,start+131071) + r=SESSION.get(url(path),headers={'Range':f'bytes={start}-{end}'},timeout=60);r.raise_for_status();assert r.status_code==206 + raw=r.content;position=start;records=[] + for line in raw.splitlines(keepends=True): + try: + row=json.loads(line);records.append((row[field],position,row)) + except (ValueError,KeyError):pass + position+=len(line) + assert records + for index,pos,row in records: + if index==target:return row + if targetrecords[-1][0]:low=records[-1][1];low_id=records[-1][0] + else:raise ValueError(f'Missing official metadata record {field}={target}') + raise ValueError(f'Lookup failed: {path} {target}') + +def keep_source(path): + dst=OUT/'reference'/path;dst.parent.mkdir(parents=True,exist_ok=True);shutil.copy2(CODE/path,dst) + +def prepare(): + from huggingface_hub import HfApi + api=HfApi();info=api.dataset_info(REPO);global SOURCE_REV;SOURCE_REV=info.sha + code_rev=subprocess.check_output(['git','-C',str(CODE),'rev-parse','HEAD'],text=True).strip() + tasks=[];samples=[] + if REFLEX: + table=pq.read_table(WORK/'episodes-file-000.parquet') + columns=[c for c in table.column_names if not c.startswith('stats/')] + eps=table.select(columns).to_pylist();official=pq.read_table(WORK/'tasks.parquet').to_pylist() + keys=['ball_catching','conveyor_belt_pick_and_place','whack_a_mole','rolling_ball_interception','ball_throwing','rotating_peg_insertion'] + descriptions=['Catch a launched ball with a held container.','Pick from the moving conveyor and release into the bin.','Strike the active mole using the closed gripper during its popup window.','Intercept the ball or orange rolling down the ramp.','Throw the pre-grasped ball into the target bin.','Time peg insertion into the moving hole of a rotating disc.'] + rules=[ + 'Episode success is task_phase == 4. The ball must remain in the virtual catch zone below the end effector for the configured consecutive-step threshold.', + 'Success requires the object inside the bin in environment-local coordinates: x in [-0.2,0.2], y in [-0.6,-0.3], z in [0.0,0.08] m.', + 'Unified evaluation success is valid_hits > 0. A valid hit requires proximity to the active mole, closed gripper and the configured dwell. Current eval profile uses 2.0 s popup, 0.3 s gap, 0 s initial delay and 3.0 s evaluation length. Completing the window schedule alone is not success.', + 'Episode success is task_phase == 4. The rolling object must stay in the virtual catch zone for the configured hold threshold.', + 'Success is task_phase == 2, meaning the ball entered the target bin. Documentation bounds relative to bin center: |x-cx| <= 0.13, |y-cy| <= 0.09, z in [0.02,0.18] m.', + 'Success is task_phase == 4. Peg tip enters the hole within its radius tolerance, descends at least 0.02 m below the disc surface, and holds for at least 5 control steps (task README).'] + profiles_source=(CODE/'scripts/evaluation/task_profiles.py').read_text(encoding='utf-8') + profiles=next(ast.literal_eval(n.value) for n in ast.parse(profiles_source).body if isinstance(n,ast.AnnAssign) and getattr(n.target,'id','')=='TASK_PROFILES') + for item,key,desc,rule in zip(official,keys,descriptions,rules): + index=item['task_index'];local=[e for e in eps if e['tasks']==[item['task']]] + relative=f'source/reflexbench/reflexbench/tasks/manager_based/{key}/README.md' + task=dict(task_index=index,key=key,name=key.replace('_',' ').title(),category='Reaction-critical',instruction=item['task'],description=desc,success_rule=rule,profile=profiles[key],official_gym_id=profiles[key]['gym_id'],doc_url=f'https://github.com/{GITHUB}/blob/{code_rev}/{relative}',published_episode_count=len(local)) + tasks.append(task);keep_source(relative) + for j in [0,len(local)//2,len(local)-1]: + ep=local[j];eid=ep['episode_index'];views=[] + for camera,label in [('fixed_cam','FIXED CAMERA'),('wrist_cam','WRIST CAMERA')]: + prefix=f'videos/observation.images.{camera}' + path=f"{prefix}/chunk-{ep[prefix+'/chunk_index']:03d}/file-{ep[prefix+'/file_index']:03d}.mp4" + obj=api.get_paths_info(REPO,[path],repo_type='dataset',revision=SOURCE_REV)[0] + views.append(dict(camera=camera,label=label,path=f'media/{key}/episode_{eid:06d}/{camera}.mp4',source_path=path,source_bytes=obj.size,from_timestamp=ep[prefix+'/from_timestamp'],to_timestamp=ep[prefix+'/to_timestamp'])) + samples.append(dict(task_index=index,task_key=key,episode_index=eid,frame_count=ep['length'],fps=25,instruction=item['task'],metadata=ep,views=views,trajectory_path=f'trajectories/{key}/episode_{eid:06d}.parquet',composite_path=f'media/{key}/episode_{eid:06d}/synchronized.mp4',preview_path=f'media/{key}/episode_{eid:06d}/preview.jpg')) + for f in ['scripts/evaluation/task_profiles.py','scripts/data_collection/task_prompts.py']:keep_source(f) + shutil.copy2(WORK/'tasks.parquet',OUT/'provenance'/'official_tasks.parquet') + note='Six official task_index values 0–5. Single Franka arm; only fixed_cam and wrist_cam exist. Do not relabel the wrist as left/right. Success rules describe evaluation, not an unprovided per-demo score.' + else: + # Metadata-only range sampling. Two episodes from each distant window. + windows={'long_horizon':['episode-window-0.json'], 'pick':['episode-window-0.08.json','episode-window-0.3.json','episode-window-0.42.json'],'place':['episode-window-0.54.json','episode-window-0.78.json','episode-window-0.999.json']} + selected=[] + for kind,files in windows.items(): + for filename in files: + xs=read(WORK/filename) + positions=[0,200,400,600,800,1000] if kind=='long_horizon' else [50,len(xs)-51] + selected.extend(xs[i] for i in positions) + for ep in selected: + eid=ep['episode_index'];path=f'data/chunk-{eid//1000:03d}/episode_{eid:06d}.parquet';local=WORK/f'episode_{eid:06d}.parquet';download_file(path,local);table=pq.read_table(local);ids=set(table['task_index'].to_pylist());assert len(ids)==1;index=ids.pop();assert set(table['episode_index'].to_pylist())=={eid};assert table.num_rows==ep['length'] + task_meta=lookup_jsonl('meta/tasks.jsonl',index,'task_index',63111962);assert task_meta['task']==ep['tasks'];meta=json.loads(ep['tasks']);kind=meta['task'];cam=lookup_jsonl('meta/camera.jsonl',eid,'episode_index',173353120) + obj=meta['objects'][0];container=meta.get('containers',[''])[0] + instruction=f'Pick up the {obj}.' if kind=='pick' else f'Pick up the {obj} and place it in/on the {container}.' + # This deterministic sentence is a readable rendering, not a recorded literal prompt. + rule='Success requires object-to-end-effector distance < tolerance and end-effector-to-configured-goal distance < tolerance. The current default tolerance is 0.015 m; per-scene overrides may differ.' if kind=='pick' else 'Success requires ALL target objects to satisfy the container-relative geometric placement check, and the end effector to return within tolerance of the configured goal. Current default return tolerance is 0.015 m; per-scene overrides may differ.' + key=f'task_{index:06d}' + task=dict(task_index=index,key=key,name=f'{kind.replace("_"," ").title()} · {obj}',category={'pick':'Pick','place':'Place','long_horizon':'Long-Horizon'}[kind],instruction=instruction,instruction_note='Readable deterministic rendering of structured official instruction metadata; the exact generated natural-language variant is not stored.',instruction_metadata=meta,description=f'Official DOM simulation scenario {cam["filename"]}. Object/container aliases are preserved in the metadata.',success_rule=rule,doc_url=f'https://github.com/{GITHUB}/blob/{code_rev}/simulations/configs/termination_cfg.py',source_filename=cam['filename'],published_episode_count=None) + if index not in {t['task_index'] for t in tasks}:tasks.append(task) + views=[dict(camera=c,label=label,path=f'media/{key}/episode_{eid:06d}/{c}.mp4',source_path=f'videos/chunk-{eid//1000:03d}/observation.images.{c}/episode_{eid:06d}.mp4') for c,label in [('opst_cam','OPPOSITE CAMERA'),('wrist_cam','WRIST CAMERA'),('side_cam','SIDE CAMERA')]] + samples.append(dict(task_index=index,task_key=key,episode_index=eid,frame_count=ep['length'],fps=25,instruction=instruction,instruction_metadata=meta,official_task_record=task_meta,camera_metadata=cam,source_filename=cam['filename'],views=views,trajectory_source_path=path,trajectory_path=f'trajectories/{key}/episode_{eid:06d}.parquet',composite_path=f'media/{key}/episode_{eid:06d}/synchronized.mp4',preview_path=f'media/{key}/episode_{eid:06d}/preview.jpg')) + print(f'Mapped {kind} task_index={index} episode_index={eid} ({cam["filename"]})',flush=True) + for f in ['simulations/configs/termination_cfg.py','utils/instruction_generator.py','simulations/helpers.py','simulations/configs/sim_cfg.yaml']:keep_source(f) + note='DOM has 3 task families, not 3 task_index values: 140,932 structured instruction IDs and 207,306 episodes. This subset selects 6 demonstrations per family (18 total), preserving actual task_index/episode_index and structured instructions. All 3 published cameras are single-arm cameras: opposite, wrist, side, not top/left/right arms.' + keep_source('LICENSE');keep_source('README.md') + shutil.copy2(CODE/'LICENSE',OUT/'LICENSE') + write(OUT/'provenance/tasks.json',tasks);write(OUT/'provenance/samples.json',samples) + source=dict(benchmark=NAME,repo_id=REPO,revision=SOURCE_REV,code_repository=GITHUB,code_revision=code_rev,note=note,date='2026-10-03',video_policy='Complete selected episodes, converted to browser-friendly H.264 MP4 at original 25 FPS. No generated simulation rollouts.',actual_episode_score='Not published in released LeRobot features; null, not assumed successful.',episode_selection='First/middle/last episode per official task' if REFLEX else 'Two episodes from three spaced metadata windows for pick/place, six spaced long-horizon scenarios.',camera_order=[v['camera'] for v in samples[0]['views']]) + write(OUT/'provenance/source.json',source);shutil.copy2(WORK/'info.json',OUT/'provenance/official_info.json');print(note,flush=True) + +def encode_frames(frames,path): + import av + path.parent.mkdir(parents=True,exist_ok=True) + with av.open(str(path),'w') as output: + stream=None;count=0 + for frame in frames: + if stream is None: + stream=output.add_stream('libx264',rate=25);stream.width=frame.width;stream.height=frame.height;stream.pix_fmt='yuv420p';stream.options={'crf':'18','preset':'fast'} + frame=frame.reformat(format='yuv420p');frame.pts=count;frame.time_base=Fraction(1,25) + for packet in stream.encode(frame):output.mux(packet) + count+=1 + if stream is None:raise ValueError('No frames extracted') + for packet in stream.encode():output.mux(packet) + return count + +def download(): + import av + source=read(OUT/'provenance/source.json');samples=read(OUT/'provenance/samples.json');summary=[] + if REFLEX: + path='data/chunk-000/file-000.parquet';download_file(path,WORK/'trajectories.parquet');data=pq.read_table(WORK/'trajectories.parquet') + for s in samples: + table=data.filter(pa.compute.equal(data['episode_index'],s['episode_index']));assert table.num_rows==s['frame_count'];assert set(table['task_index'].to_pylist())=={s['task_index']};target=OUT/s['trajectory_path'];target.parent.mkdir(parents=True,exist_ok=True);pq.write_table(table,target) + for view_index in range(2): + model=samples[0]['views'][view_index];reader=RangeReader(model['source_path'],model['source_bytes']);container=av.open(reader);stream=container.streams.video[0] + for s in sorted(samples,key=lambda s:s['episode_index']): + view=s['views'][view_index];target=OUT/view['path'] + if target.exists():continue + start=view['from_timestamp'];container.seek(int(start/stream.time_base),stream=stream,backward=True) + def frames(): + found=0 + for f in container.decode(stream): + if f.time+0.00001=s['frame_count']:break + yield f;found+=1 + assert found==s['frame_count'],(s['episode_index'],found,s['frame_count']) + n=encode_frames(frames(),target);view['output_sha256']=hashlib.sha256(target.read_bytes()).hexdigest();print('Extracted',view['camera'],s['episode_index'],n,'frames',flush=True) + container.close();summary.append({'source_path':model['source_path'],'source_shard_size':reader.size,'range_bytes_received':reader.transferred}) + else: + def run(s): + target=OUT/s['trajectory_path'];target.parent.mkdir(parents=True,exist_ok=True);shutil.copy2(WORK/f"episode_{s['episode_index']:06d}.parquet",target) + for v in s['views']: + original=WORK/f"{s['episode_index']:06d}-{v['camera']}.mp4";download_file(v['source_path'],original) + dst=OUT/v['path'];dst.parent.mkdir(parents=True,exist_ok=True) + if not dst.exists(): + subprocess.run(['ffmpeg','-v','error','-y','-i',str(original),'-c:v','libx264','-crf','18','-preset','fast','-pix_fmt','yuv420p','-movflags','+faststart',str(dst)],check=True,capture_output=True) + v['source_sha256']=hashlib.sha256(original.read_bytes()).hexdigest();v['source_bytes']=original.stat().st_size;v['output_sha256']=hashlib.sha256(dst.read_bytes()).hexdigest() + print('Downloaded/transcoded',s['episode_index'],flush=True) + with cf.ThreadPoolExecutor(max_workers=4) as ex:list(ex.map(run,samples)) + summary=[dict(source_video_files=sum(len(s['views']) for s in samples),source_video_bytes=sum(v['source_bytes'] for s in samples for v in s['views']))] + write(OUT/'provenance/samples.json',samples);write(OUT/'provenance/download_report.json',dict(details=summary,whole_repo_downloaded=False,assets_downloaded=False,checkpoints_downloaded=False)) + +def render(): + from PIL import Image,ImageDraw + samples=read(OUT/'provenance/samples.json');n=len(samples[0]['views']);labels=Image.new('RGB',(320*n,28),'#14251e');draw=ImageDraw.Draw(labels) + for i,v in enumerate(samples[0]['views']):draw.text((i*320+10,8),v['label'],fill='white') + label_path=WORK/'labels.png';labels.save(label_path) + def run(s): + target=OUT/s['composite_path'];target.parent.mkdir(parents=True,exist_ok=True) + if not target.exists(): + height=320 if REFLEX else 240;cmd=['ffmpeg','-v','error','-y'] + for v in s['views']:cmd+=['-i',str(OUT/v['path'])] + cmd+=['-loop','1','-i',str(label_path)] + filters=';'.join(f'[{i}:v]scale=320:{height},setsar=1[c{i}]' for i in range(n))+f';'+''.join(f'[c{i}]' for i in range(n))+f'hstack=inputs={n}[v];[{n}:v]format=yuv420p[l];[l][v]vstack=inputs=2:shortest=1[out]' + cmd+=['-filter_complex',filters,'-map','[out]','-c:v','libx264','-crf','21','-preset','fast','-pix_fmt','yuv420p','-frames:v',str(s['frame_count']),'-r','25','-movflags','+faststart',str(target)];subprocess.run(cmd,check=True,capture_output=True) + subprocess.run(['ffmpeg','-v','error','-y','-i',str(target),'-frames:v','1','-q:v','2',str(OUT/s['preview_path'])],check=True,capture_output=True) + with cf.ThreadPoolExecutor(max_workers=3) as ex:list(ex.map(run,samples)) + checks=[] + for s in samples: + table=pq.read_table(OUT/s['trajectory_path']);assert table.num_rows==s['frame_count'];assert set(table['task_index'].to_pylist())=={s['task_index']} + frames=[] + for path in [v['path'] for v in s['views']]+[s['composite_path']]: + r=json.loads(subprocess.check_output(['ffprobe','-v','error','-select_streams','v:0','-show_entries','stream=codec_name,width,height,nb_frames,duration','-of','json',str(OUT/path)],text=True))['streams'][0] + assert r['codec_name']=='h264' and int(r['nb_frames'])==s['frame_count'],(path,r,s['frame_count']);frames.append(dict(path=path,**r)) + checks.append(dict(task_index=s['task_index'],episode_index=s['episode_index'],videos=frames)) + write(OUT/'provenance/validation.json',dict(passed=True,episodes=len(samples),checks=checks));print('Verified full frame counts, task IDs and H.264 MP4:',len(samples),'episodes',flush=True) + +def package(): + import yaml + from datasets import Dataset,Features,Value,Video,Image + tasks=read(OUT/'provenance/tasks.json');samples=read(OUT/'provenance/samples.json');source=read(OUT/'provenance/source.json');rows=[] + for s in samples: + t=next(t for t in tasks if t['task_index']==s['task_index']) + row=dict(task_index=s['task_index'],task_name=t['name'],category=t['category'],episode_index=s['episode_index'],synchronized= {'path':f'hf://datasets/{DEST}@main/'+s['composite_path'],'bytes':None}) + for v in s['views']:row[v['camera']]={'path':f'hf://datasets/{DEST}@main/'+v['path'],'bytes':None} + row.update(instruction=s['instruction'],instruction_metadata=json.dumps(s.get('instruction_metadata'),ensure_ascii=False),success_rule=t['success_rule'],actual_episode_success=None,frame_count=s['frame_count'],fps=25,duration_seconds=s['frame_count']/25,source_repo=REPO,source_revision=source['revision'],trajectory_url=f'https://huggingface.co/datasets/{DEST}/resolve/main/'+s['trajectory_path'],official_doc=t['doc_url'],source_filename=s.get('source_filename',''),camera_metadata=json.dumps(s.get('camera_metadata'),ensure_ascii=False)) + rows.append(row) + video_columns=['synchronized']+source['camera_order'];features=Features({k:Video(decode=False) if k in video_columns else Value('int64') if k in ['task_index','episode_index','frame_count','fps'] else Value('float64') if k=='duration_seconds' else Value('bool') if k=='actual_episode_success' else Value('string') for k in rows[0]}) + ds=Dataset.from_list(rows,features=features);(OUT/'data').mkdir(exist_ok=True);configs=[] + def subset(name,indices,default=False): + p=f'data/{name}.parquet';ds.select(indices).to_parquet(str(OUT/p),batch_size=32);entry=dict(config_name=name,data_files=[dict(split='examples',path=p)]) + if default:entry['default']=True + configs.append(entry) + subset('all',list(range(len(rows))),True) + for t in tasks:subset(f"task_{t['task_index']:06d}",[i for i,r in enumerate(rows) if r['task_index']==t['task_index']]) + for category in sorted({t['category'] for t in tasks}):subset(category.lower().replace('-','_'),[i for i,r in enumerate(rows) if r['category']==category]) + header=dict(language=['en','zh'],license='bsd-3-clause' if REFLEX else 'other',pretty_name=NAME+' Simulation Task Examples',configs=configs,tags=['robotics','video','simulation']) + if not REFLEX:header.update(license_name='slab-license',license_link='LICENSE') + browser=f'https://travor278-{NAME.lower()}-task-examples.static.hf.space' + lines=['---',yaml.safe_dump(header,sort_keys=False,allow_unicode=True).rstrip(),'---',f'# {NAME} Simulation Task Examples',f'\n[打开 MP4 任务浏览页]({browser}/?task={tasks[0]["task_index"]})', '\n'+source['note'], + '\n所有示例是完整 H.264 MP4。单臂相机保留官方名称：'+ ' / '.join(source['camera_order'])+'。每条有同步合并视频、各路原视频与官方动作/状态 Parquet。', + '\n评估标准根据官方代码和文档整理；发布数据未保存逐条示教 success 标签，故 actual_episode_success 为 null。本文不编造 0–100 得分。', + '\n| 官方 task_index | Task / instruction scenario | 分类 | 直接浏览 |','|---|---|---|---|'] + for t in sorted(tasks,key=lambda t:t['task_index']):lines.append(f"| {t['task_index']} | {t['name']} | {t['category']} | [打开]({browser}/?task={t['task_index']}) |") + for t in tasks: + lines.extend([f"\n## task_index={t['task_index']} · {t['name']}",f"\n**Instruction:** {t['instruction']}",f"\n**Description:** {t['description']}",f"\n**Success / evaluation:** {t['success_rule']}",f"\n[官方说明]({t['doc_url']})"]) + if t.get('instruction_metadata'):lines.extend(['\n结构化原始 instruction（完整别名）：','\n```json',json.dumps(t['instruction_metadata'],ensure_ascii=False,indent=2),'```','\n'+t['instruction_note']]) + if t.get('official_gym_id'):lines.append(f"\n**Gym ID:** `{t['official_gym_id']}`") + for s in [s for s in samples if s['task_index']==t['task_index']]:lines.extend([f"\n**episode_index={s['episode_index']}** · {s['frame_count']} frames / {s['frame_count']/25:.2f} s",f"\n![Camera preview]({s['preview_path']})",f"\n[同步 MP4]({s['composite_path']}) · "+' · '.join(f"[{v['camera']} MP4]({v['path']})" for v in s['views'])+f" · [官方轨迹]({s['trajectory_path']})"]) + lines.extend(['\n## 来源、许可与复现',f'\n官方数据：[原仓库](https://huggingface.co/datasets/{REPO}) · 固定 revision `{source["revision"]}`。',f'\n官方代码：[GitHub](https://github.com/{GITHUB}) · revision `{source["code_revision"]}`。','\n保留上游 LICENSE 和来源文件在 `reference/`。ReflexBench 官方数据未单列许可证元数据；保留官方实现 BSD-3-Clause 来源，不扩大作者权利。' if REFLEX else '\n遵循上游 S-Lab License 1.0，仅允许非商业用途；见 LICENSE。','\n选择性提取记录、原始时间区间、task/episode 对应、相机元数据和校验均在 `provenance/`。不下载场景资产、模型权重或完整数据仓库。','\n复现脚本：`scripts/build_examples.py`。浏览页源码另见 `browser/` 和 `scripts/build_browser.py`。']) + (OUT/'README.md').write_text('\n'.join(lines)+'\n',encoding='utf-8');(OUT/'scripts').mkdir(exist_ok=True);shutil.copy2(__file__,OUT/'scripts/build_examples.py');print('Packaged',len(rows),'rows,',len(configs),'native HF subsets',flush=True) + +if __name__=='__main__': + WORK.mkdir(exist_ok=True);(OUT/'provenance').mkdir(parents=True,exist_ok=True) + if (OUT/'provenance/source.json').exists():SOURCE_REV=read(OUT/'provenance/source.json')['revision'] + globals()[sys.argv[1]]() diff --git a/trajectories/ball_catching/episode_000000.parquet b/trajectories/ball_catching/episode_000000.parquet new file mode 100644 index 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