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meta/data_config.py

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+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from abc import ABC, abstractmethod
+
+from gr00t.data.dataset import ModalityConfig
+from gr00t.data.transform.base import ComposedModalityTransform, ModalityTransform
+from gr00t.data.transform.concat import ConcatTransform
+from gr00t.data.transform.state_action import StateActionToTensor, StateActionTransform
+from gr00t.data.transform.video import (
+    VideoColorJitter,
+    VideoCrop,
+    VideoResize,
+    VideoToNumpy,
+    VideoToTensor,
+)
+from gr00t.model.transforms import GR00TTransform
+
+
+class BaseDataConfig(ABC):
+    @abstractmethod
+    def modality_config(self) -> dict[str, ModalityConfig]:
+        pass
+
+    @abstractmethod
+    def transform(self) -> ModalityTransform:
+        pass
+
+
+###########################################################################################
+
+
+class Gr1ArmsOnlyDataConfig(BaseDataConfig):
+    video_keys = ["video.ego_view"]
+    state_keys = [
+        "state.left_arm",
+        "state.right_arm",
+        "state.left_hand",
+        "state.right_hand",
+    ]
+    action_keys = [
+        "action.left_arm",
+        "action.right_arm",
+        "action.left_hand",
+        "action.right_hand",
+    ]
+    language_keys = ["annotation.human.action.task_description"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self) -> dict[str, ModalityConfig]:
+        video_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.video_keys,
+        )
+
+        state_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.state_keys,
+        )
+
+        action_modality = ModalityConfig(
+            delta_indices=self.action_indices,
+            modality_keys=self.action_keys,
+        )
+
+        language_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.language_keys,
+        )
+
+        modality_configs = {
+            "video": video_modality,
+            "state": state_modality,
+            "action": action_modality,
+            "language": language_modality,
+        }
+
+        return modality_configs
+
+    def transform(self) -> ModalityTransform:
+        transforms = [
+            # video transforms
+            VideoToTensor(apply_to=self.video_keys),
+            VideoCrop(apply_to=self.video_keys, scale=0.95),
+            VideoResize(apply_to=self.video_keys, height=224, width=224, interpolation="linear"),
+            VideoColorJitter(
+                apply_to=self.video_keys,
+                brightness=0.3,
+                contrast=0.4,
+                saturation=0.5,
+                hue=0.08,
+            ),
+            VideoToNumpy(apply_to=self.video_keys),
+            # state transforms
+            StateActionToTensor(apply_to=self.state_keys),
+            StateActionTransform(
+                apply_to=self.state_keys,
+                normalization_modes={key: "min_max" for key in self.state_keys},
+            ),
+            # action transforms
+            StateActionToTensor(apply_to=self.action_keys),
+            StateActionTransform(
+                apply_to=self.action_keys,
+                normalization_modes={key: "min_max" for key in self.action_keys},
+            ),
+            # concat transforms
+            ConcatTransform(
+                video_concat_order=self.video_keys,
+                state_concat_order=self.state_keys,
+                action_concat_order=self.action_keys,
+            ),
+            # model-specific transform
+            GR00TTransform(
+                state_horizon=len(self.observation_indices),
+                action_horizon=len(self.action_indices),
+                max_state_dim=64,
+                max_action_dim=32,
+            ),
+        ]
+        return ComposedModalityTransform(transforms=transforms)
+
+
+###########################################################################################
+
+
+class So100DataConfig(BaseDataConfig):
+    video_keys = ["video.webcam"]
+    state_keys = ["state.single_arm", "state.gripper"]
+    action_keys = ["action.single_arm", "action.gripper"]
+    language_keys = ["annotation.human.task_description"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self) -> dict[str, ModalityConfig]:
+        video_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.video_keys,
+        )
+
+        state_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.state_keys,
+        )
+
+        action_modality = ModalityConfig(
+            delta_indices=self.action_indices,
+            modality_keys=self.action_keys,
+        )
+
+        language_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.language_keys,
+        )
+
+        modality_configs = {
+            "video": video_modality,
+            "state": state_modality,
+            "action": action_modality,
+            "language": language_modality,
+        }
+
+        return modality_configs
+
+    def transform(self) -> ModalityTransform:
+        transforms = [
+            # video transforms
+            VideoToTensor(apply_to=self.video_keys),
+            VideoCrop(apply_to=self.video_keys, scale=0.95),
+            VideoResize(apply_to=self.video_keys, height=224, width=224, interpolation="linear"),
+            VideoColorJitter(
+                apply_to=self.video_keys,
+                brightness=0.3,
+                contrast=0.4,
+                saturation=0.5,
+                hue=0.08,
+            ),
+            VideoToNumpy(apply_to=self.video_keys),
+            # state transforms
+            StateActionToTensor(apply_to=self.state_keys),
+            StateActionTransform(
+                apply_to=self.state_keys,
+                normalization_modes={key: "min_max" for key in self.state_keys},
+            ),
+            # action transforms
+            StateActionToTensor(apply_to=self.action_keys),
+            StateActionTransform(
+                apply_to=self.action_keys,
+                normalization_modes={key: "min_max" for key in self.action_keys},
+            ),
+            # concat transforms
+            ConcatTransform(
+                video_concat_order=self.video_keys,
+                state_concat_order=self.state_keys,
+                action_concat_order=self.action_keys,
+            ),
+            # model-specific transform
+            GR00TTransform(
+                state_horizon=len(self.observation_indices),
+                action_horizon=len(self.action_indices),
+                max_state_dim=64,
+                max_action_dim=32,
+            ),
+        ]
+        return ComposedModalityTransform(transforms=transforms)
+
+
+###########################################################################################
+
+
+class Gr1FullUpperBodyDataConfig(BaseDataConfig):
+    video_keys = ["video.front_view"]
+    state_keys = [
+        "state.left_arm",
+        "state.right_arm",
+        "state.left_hand",
+        "state.right_hand",
+        "state.waist",
+        "state.neck",
+    ]
+    action_keys = [
+        "action.left_arm",
+        "action.right_arm",
+        "action.left_hand",
+        "action.right_hand",
+        "action.waist",
+        "action.neck",
+    ]
+    language_keys = ["annotation.human.action.task_description"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self):
+        video_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.video_keys,
+        )
+        state_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.state_keys,
+        )
+        action_modality = ModalityConfig(
+            delta_indices=self.action_indices,
+            modality_keys=self.action_keys,
+        )
+        language_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.language_keys,
+        )
+        modality_configs = {
+            "video": video_modality,
+            "state": state_modality,
+            "action": action_modality,
+            "language": language_modality,
+        }
+        return modality_configs
+
+    def transform(self):
+        transforms = [
+            # video transforms
+            VideoToTensor(apply_to=self.video_keys),
+            VideoCrop(apply_to=self.video_keys, scale=0.95),
+            VideoResize(apply_to=self.video_keys, height=224, width=224, interpolation="linear"),
+            VideoColorJitter(
+                apply_to=self.video_keys,
+                brightness=0.3,
+                contrast=0.4,
+                saturation=0.5,
+                hue=0.08,
+            ),
+            VideoToNumpy(apply_to=self.video_keys),
+            # state transforms
+            StateActionToTensor(apply_to=self.state_keys),
+            StateActionTransform(
+                apply_to=self.state_keys,
+                normalization_modes={
+                    "state.left_arm": "min_max",
+                    "state.right_arm": "min_max",
+                    "state.left_hand": "min_max",
+                    "state.right_hand": "min_max",
+                    "state.waist": "min_max",
+                    "state.neck": "min_max",
+                },
+            ),
+            # action transforms
+            StateActionToTensor(apply_to=self.action_keys),
+            StateActionTransform(
+                apply_to=self.action_keys,
+                normalization_modes={
+                    "action.right_arm": "min_max",
+                    "action.left_arm": "min_max",
+                    "action.right_hand": "min_max",
+                    "action.left_hand": "min_max",
+                    "action.waist": "min_max",
+                    "action.neck": "min_max",
+                },
+            ),
+            # concat transforms
+            ConcatTransform(
+                video_concat_order=self.video_keys,
+                state_concat_order=self.state_keys,
+                action_concat_order=self.action_keys,
+            ),
+            GR00TTransform(
+                state_horizon=len(self.observation_indices),
+                action_horizon=len(self.action_indices),
+                max_state_dim=64,
+                max_action_dim=32,
+            ),
+        ]
+
+        return ComposedModalityTransform(transforms=transforms)
+
+
+###########################################################################################
+
+
+class BimanualPandaGripperDataConfig(BaseDataConfig):
+    video_keys = [
+        "video.right_wrist_view",
+        "video.left_wrist_view",
+        "video.front_view",
+    ]
+    state_keys = [
+        "state.right_arm_eef_pos",
+        "state.right_arm_eef_quat",
+        "state.right_gripper_qpos",
+        "state.left_arm_eef_pos",
+        "state.left_arm_eef_quat",
+        "state.left_gripper_qpos",
+    ]
+    action_keys = [
+        "action.right_arm_eef_pos",
+        "action.right_arm_eef_rot",
+        "action.right_gripper_close",
+        "action.left_arm_eef_pos",
+        "action.left_arm_eef_rot",
+        "action.left_gripper_close",
+    ]
+
+    language_keys = ["annotation.human.action.task_description"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self):
+        video_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.video_keys,
+        )
+        state_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.state_keys,
+        )
+        action_modality = ModalityConfig(
+            delta_indices=self.action_indices,
+            modality_keys=self.action_keys,
+        )
+        language_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.language_keys,
+        )
+        modality_configs = {
+            "video": video_modality,
+            "state": state_modality,
+            "action": action_modality,
+            "language": language_modality,
+        }
+        return modality_configs
+
+    def transform(self):
+        transforms = [
+            # video transforms
+            VideoToTensor(apply_to=self.video_keys),
+            VideoCrop(apply_to=self.video_keys, scale=0.95),
+            VideoResize(apply_to=self.video_keys, height=224, width=224, interpolation="linear"),
+            VideoColorJitter(
+                apply_to=self.video_keys,
+                brightness=0.3,
+                contrast=0.4,
+                saturation=0.5,
+                hue=0.08,
+            ),
+            VideoToNumpy(apply_to=self.video_keys),
+            # state transforms
+            StateActionToTensor(apply_to=self.state_keys),
+            StateActionTransform(
+                apply_to=self.state_keys,
+                normalization_modes={
+                    "state.right_arm_eef_pos": "min_max",
+                    "state.right_gripper_qpos": "min_max",
+                    "state.left_arm_eef_pos": "min_max",
+                    "state.left_gripper_qpos": "min_max",
+                },
+                target_rotations={
+                    "state.right_arm_eef_quat": "rotation_6d",
+                    "state.left_arm_eef_quat": "rotation_6d",
+                },
+            ),
+            # action transforms
+            StateActionToTensor(apply_to=self.action_keys),
+            StateActionTransform(
+                apply_to=self.action_keys,
+                normalization_modes={
+                    "action.right_gripper_close": "binary",
+                    "action.left_gripper_close": "binary",
+                },
+            ),
+            # concat transforms
+            ConcatTransform(
+                video_concat_order=self.video_keys,
+                state_concat_order=self.state_keys,
+                action_concat_order=self.action_keys,
+            ),
+            GR00TTransform(
+                state_horizon=len(self.observation_indices),
+                action_horizon=len(self.action_indices),
+                max_state_dim=64,
+                max_action_dim=32,
+            ),
+        ]
+
+        return ComposedModalityTransform(transforms=transforms)
+
+
+###########################################################################################
+
+
+class BimanualPandaHandDataConfig(BaseDataConfig):
+    video_keys = [
+        "video.right_wrist_view",
+        "video.left_wrist_view",
+        "video.ego_view",
+    ]
+    state_keys = [
+        "state.right_arm_eef_pos",
+        "state.right_arm_eef_quat",
+        "state.right_hand",
+        "state.left_arm_eef_pos",
+        "state.left_arm_eef_quat",
+        "state.left_hand",
+    ]
+    action_keys = [
+        "action.right_arm_eef_pos",
+        "action.right_arm_eef_rot",
+        "action.right_hand",
+        "action.left_arm_eef_pos",
+        "action.left_arm_eef_rot",
+        "action.left_hand",
+    ]
+    language_keys = ["annotation.human.action.task_description"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self):
+        video_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.video_keys,
+        )
+        state_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.state_keys,
+        )
+        action_modality = ModalityConfig(
+            delta_indices=self.action_indices,
+            modality_keys=self.action_keys,
+        )
+        language_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.language_keys,
+        )
+        modality_configs = {
+            "video": video_modality,
+            "state": state_modality,
+            "action": action_modality,
+            "language": language_modality,
+        }
+        return modality_configs
+
+    def transform(self):
+        transforms = [
+            # video transforms
+            VideoToTensor(apply_to=self.video_keys),
+            VideoCrop(apply_to=self.video_keys, scale=0.95),
+            VideoResize(apply_to=self.video_keys, height=224, width=224, interpolation="linear"),
+            VideoColorJitter(
+                apply_to=self.video_keys,
+                brightness=0.3,
+                contrast=0.4,
+                saturation=0.5,
+                hue=0.08,
+            ),
+            VideoToNumpy(apply_to=self.video_keys),
+            # state transforms
+            StateActionToTensor(apply_to=self.state_keys),
+            StateActionTransform(
+                apply_to=self.state_keys,
+                normalization_modes={
+                    "state.right_arm_eef_pos": "min_max",
+                    "state.right_hand": "min_max",
+                    "state.left_arm_eef_pos": "min_max",
+                    "state.left_hand": "min_max",
+                },
+                target_rotations={
+                    "state.right_arm_eef_quat": "rotation_6d",
+                    "state.left_arm_eef_quat": "rotation_6d",
+                },
+            ),
+            # action transforms
+            StateActionToTensor(apply_to=self.action_keys),
+            StateActionTransform(
+                apply_to=self.action_keys,
+                normalization_modes={
+                    "action.right_hand": "min_max",
+                    "action.left_hand": "min_max",
+                },
+            ),
+            # concat transforms
+            ConcatTransform(
+                video_concat_order=self.video_keys,
+                state_concat_order=self.state_keys,
+                action_concat_order=self.action_keys,
+            ),
+            GR00TTransform(
+                state_horizon=len(self.observation_indices),
+                action_horizon=len(self.action_indices),
+                max_state_dim=64,
+                max_action_dim=32,
+            ),
+        ]
+
+        return ComposedModalityTransform(transforms=transforms)
+
+
+###########################################################################################
+
+
+class SinglePandaGripperDataConfig(BaseDataConfig):
+    video_keys = [
+        "video.left_view",
+        "video.right_view",
+        "video.wrist_view",
+    ]
+    state_keys = [
+        "state.end_effector_position_relative",
+        "state.end_effector_rotation_relative",
+        "state.gripper_qpos",
+        "state.base_position",
+        "state.base_rotation",
+    ]
+    action_keys = [
+        "action.end_effector_position",
+        "action.end_effector_rotation",
+        "action.gripper_close",
+        "action.base_motion",
+        "action.control_mode",
+    ]
+
+    language_keys = ["annotation.human.action.task_description"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self):
+        video_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.video_keys,
+        )
+        state_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.state_keys,
+        )
+        action_modality = ModalityConfig(
+            delta_indices=self.action_indices,
+            modality_keys=self.action_keys,
+        )
+        language_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.language_keys,
+        )
+        modality_configs = {
+            "video": video_modality,
+            "state": state_modality,
+            "action": action_modality,
+            "language": language_modality,
+        }
+        return modality_configs
+
+    def transform(self):
+        transforms = [
+            # video transforms
+            VideoToTensor(apply_to=self.video_keys),
+            VideoCrop(apply_to=self.video_keys, scale=0.95),
+            VideoResize(apply_to=self.video_keys, height=224, width=224, interpolation="linear"),
+            VideoColorJitter(
+                apply_to=self.video_keys,
+                brightness=0.3,
+                contrast=0.4,
+                saturation=0.5,
+                hue=0.08,
+            ),
+            VideoToNumpy(apply_to=self.video_keys),
+            # state transforms
+            StateActionToTensor(apply_to=self.state_keys),
+            StateActionTransform(
+                apply_to=self.state_keys,
+                normalization_modes={
+                    "state.end_effector_position_relative": "min_max",
+                    "state.end_effector_rotation_relative": "min_max",
+                    "state.gripper_qpos": "min_max",
+                    "state.base_position": "min_max",
+                    "state.base_rotation": "min_max",
+                },
+                target_rotations={
+                    "state.end_effector_rotation_relative": "rotation_6d",
+                    "state.base_rotation": "rotation_6d",
+                },
+            ),
+            # action transforms
+            StateActionToTensor(apply_to=self.action_keys),
+            StateActionTransform(
+                apply_to=self.action_keys,
+                normalization_modes={
+                    "action.end_effector_position": "min_max",
+                    "action.end_effector_rotation": "min_max",
+                    "action.gripper_close": "binary",
+                    "action.base_motion": "min_max",
+                    "action.control_mode": "binary",
+                },
+            ),
+            # concat transforms
+            ConcatTransform(
+                video_concat_order=self.video_keys,
+                state_concat_order=self.state_keys,
+                action_concat_order=self.action_keys,
+            ),
+            GR00TTransform(
+                state_horizon=len(self.observation_indices),
+                action_horizon=len(self.action_indices),
+                max_state_dim=64,
+                max_action_dim=32,
+            ),
+        ]
+
+        return ComposedModalityTransform(transforms=transforms)
+
+
+###########################################################################################
+
+
+class Gr1ArmsWaistDataConfig(Gr1ArmsOnlyDataConfig):
+    video_keys = ["video.ego_view"]
+    state_keys = [
+        "state.left_arm",
+        "state.right_arm",
+        "state.left_hand",
+        "state.right_hand",
+        "state.waist",
+    ]
+    action_keys = [
+        "action.left_arm",
+        "action.right_arm",
+        "action.left_hand",
+        "action.right_hand",
+        "action.waist",
+    ]
+    language_keys = ["annotation.human.coarse_action"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self):
+        return super().modality_config()
+
+    def transform(self):
+        return super().transform()
+
+
+###########################################################################################
+class LekiwiDataConfig(BaseDataConfig):
+    video_keys = ["video.wrist", "video.front"]
+    state_keys = ["state.shoulder_pan", "state.shoulder_lift", "state.elbow_flex", "state.wrist_flex", "state.wrist_roll", "state.gripper", "state.left_wheel", "state.back_wheel", "state.right_wheel"]
+    action_keys = ["action.shoulder_pan", "action.shoulder_lift", "action.elbow_flex", "action.wrist_flex", "action.wrist_roll", "action.gripper", "action.left_wheel", "action.back_wheel", "action.right_wheel"]
+    language_keys = ["annotation.human.task_description"]
+    observation_indices = [0]
+    action_indices = list(range(16))
+
+    def modality_config(self) -> dict[str, ModalityConfig]:
+        video_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.video_keys,
+        )
+
+        state_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.state_keys,
+        )
+
+        action_modality = ModalityConfig(
+            delta_indices=self.action_indices,
+            modality_keys=self.action_keys,
+        )
+
+        language_modality = ModalityConfig(
+            delta_indices=self.observation_indices,
+            modality_keys=self.language_keys,
+        )
+
+        modality_configs = {
+            "video": video_modality,
+            "state": state_modality,
+            "action": action_modality,
+            "language": language_modality,
+        }
+
+        return modality_configs
+
+    def transform(self) -> ModalityTransform:
+        transforms = [
+            # video transforms
+            VideoToTensor(apply_to=self.video_keys),
+            VideoCrop(apply_to=self.video_keys, scale=0.95),
+            VideoResize(apply_to=self.video_keys, height=224, width=224, interpolation="linear"),
+            VideoColorJitter(
+                apply_to=self.video_keys,
+                brightness=0.3,
+                contrast=0.4,
+                saturation=0.5,
+                hue=0.08,
+            ),
+            VideoToNumpy(apply_to=self.video_keys),
+            # state transforms
+            StateActionToTensor(apply_to=self.state_keys),
+            StateActionTransform(
+                apply_to=self.state_keys,
+                normalization_modes={key: "min_max" for key in self.state_keys},
+            ),
+            # action transforms
+            StateActionToTensor(apply_to=self.action_keys),
+            StateActionTransform(
+                apply_to=self.action_keys,
+                normalization_modes={key: "min_max" for key in self.action_keys},
+            ),
+            # concat transforms
+            ConcatTransform(
+                video_concat_order=self.video_keys,
+                state_concat_order=self.state_keys,
+                action_concat_order=self.action_keys,
+            ),
+            # model-specific transform
+            GR00TTransform(
+                state_horizon=len(self.observation_indices),
+                action_horizon=len(self.action_indices),
+                max_state_dim=64,
+                max_action_dim=32,
+            ),
+        ]
+        return ComposedModalityTransform(transforms=transforms)
+
+
+DATA_CONFIG_MAP = {
+    "gr1_arms_waist": Gr1ArmsWaistDataConfig(),
+    "gr1_arms_only": Gr1ArmsOnlyDataConfig(),
+    "gr1_full_upper_body": Gr1FullUpperBodyDataConfig(),
+    "bimanual_panda_gripper": BimanualPandaGripperDataConfig(),
+    "bimanual_panda_hand": BimanualPandaHandDataConfig(),
+    "single_panda_gripper": SinglePandaGripperDataConfig(),
+    "so100": So100DataConfig(),
+    "lekiwi": LekiwiDataConfig()
+}