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Modify convert_to_lerobot_v3 script for behaviours dataset to take a single task id and create a dataset outof it

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This commit is contained in:
Michel Aractingi
2025-10-24 17:06:21 +02:00
parent a52e88d349
commit fd623e0cc5
3 changed files with 203 additions and 238 deletions
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examples/behavior_1k/behaviour_1k_constants.py
+24 -9
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@@ -1,7 +1,10 @@
import numpy as np
import torch as th
from collections import OrderedDict
import numpy as np
import torch as th
ROBOT_TYPE = "R1Pro"
FPS = 30
ROBOT_CAMERA_NAMES = {
"A1": {
@@ -21,13 +24,17 @@ WRIST_RESOLUTION = (480, 480)
# TODO: Fix A1
CAMERA_INTRINSICS = {
"A1": {
"external": np.array([[306.0, 0.0, 360.0], [0.0, 306.0, 360.0], [0.0, 0.0, 1.0]], dtype=np.float32), # 240x240
"external": np.array(
[[306.0, 0.0, 360.0], [0.0, 306.0, 360.0], [0.0, 0.0, 1.0]], dtype=np.float32
), # 240x240
"wrist": np.array(
[[388.6639, 0.0, 240.0], [0.0, 388.6639, 240.0], [0.0, 0.0, 1.0]], dtype=np.float32
), # 240x240
},
"R1Pro": {
"head": np.array([[306.0, 0.0, 360.0], [0.0, 306.0, 360.0], [0.0, 0.0, 1.0]], dtype=np.float32), # 720x720
"head": np.array(
[[306.0, 0.0, 360.0], [0.0, 306.0, 360.0], [0.0, 0.0, 1.0]], dtype=np.float32
), # 720x720
"left_wrist": np.array(
[[388.6639, 0.0, 240.0], [0.0, 388.6639, 240.0], [0.0, 0.0, 1.0]], dtype=np.float32
), # 480x480
@@ -48,7 +55,7 @@ BEHAVIOR_DATASET_FEATURES = {
},
# Proprioception
"observation.state": {
"dtype": "float32",
"dtype": "float32",
"shape": (256,), # Full proprioception state
"names": None,
},
@@ -229,7 +236,10 @@ JOINT_RANGE = {
"gripper": (th.tensor([0.00], dtype=th.float32), th.tensor([0.03], dtype=th.float32)),
},
"R1Pro": {
"base": (th.tensor([-0.75, -0.75, -1.0], dtype=th.float32), th.tensor([0.75, 0.75, 1.0], dtype=th.float32)),
"base": (
th.tensor([-0.75, -0.75, -1.0], dtype=th.float32),
th.tensor([0.75, 0.75, 1.0], dtype=th.float32),
),
"torso": (
th.tensor([-1.1345, -2.7925, -1.8326, -3.0543], dtype=th.float32),
th.tensor([1.8326, 2.5307, 1.5708, 3.0543], dtype=th.float32),
@@ -253,8 +263,14 @@ EEF_POSITION_RANGE = {
"0": (th.tensor([0.0, -0.7, 0.0], dtype=th.float32), th.tensor([0.7, 0.7, 0.7], dtype=th.float32)),
},
"R1Pro": {
"left": (th.tensor([0.0, -0.65, 0.0], dtype=th.float32), th.tensor([0.65, 0.65, 2.5], dtype=th.float32)),
"right": (th.tensor([0.0, -0.65, 0.0], dtype=th.float32), th.tensor([0.65, 0.65, 2.5], dtype=th.float32)),
"left": (
th.tensor([0.0, -0.65, 0.0], dtype=th.float32),
th.tensor([0.65, 0.65, 2.5], dtype=th.float32),
),
"right": (
th.tensor([0.0, -0.65, 0.0], dtype=th.float32),
th.tensor([0.65, 0.65, 2.5], dtype=th.float32),
),
},
}
@@ -317,4 +333,3 @@ TASK_NAMES_TO_INDICES = {
"make_pizza": 49,
}
TASK_INDICES_TO_NAMES = {v: k for k, v in TASK_NAMES_TO_INDICES.items()}