diff --git a/ddlitlab2024/dataset/models.py b/ddlitlab2024/dataset/models.py
index a4a6042..3bfb271 100644
--- a/ddlitlab2024/dataset/models.py
+++ b/ddlitlab2024/dataset/models.py
@@ -214,6 +214,31 @@ class JointStates(Base):
         Index(None, "recording_id", asc("stamp")),
     )
 
+    def get_ordered_joint_names(self) -> list[str]:
+        return [
+            JointStates.head_pan.name,
+            JointStates.head_tilt.name,
+            JointStates.l_ankle_pitch.name,
+            JointStates.l_ankle_roll.name,
+            JointStates.l_elbow.name,
+            JointStates.l_hip_pitch.name,
+            JointStates.l_hip_roll.name,
+            JointStates.l_hip_yaw.name,
+            JointStates.l_knee.name,
+            JointStates.l_shoulder_pitch.name,
+            JointStates.l_shoulder_roll.name,
+            JointStates.r_ankle_pitch.name,
+            JointStates.r_ankle_roll.name,
+            JointStates.r_elbow.name,
+            JointStates.r_hip_pitch.name,
+            JointStates.r_hip_roll.name,
+            JointStates.r_hip_yaw.name,
+            JointStates.r_knee.name,
+            JointStates.r_shoulder_pitch.name,
+            JointStates.r_shoulder_roll.name,
+            # TODO add new NAO joints
+        ]
+
 
 class JointCommands(Base):
     __tablename__ = "JointCommands"
diff --git a/ddlitlab2024/dataset/pytorch.py b/ddlitlab2024/dataset/pytorch.py
index 9a3e424..6fd12cb 100755
--- a/ddlitlab2024/dataset/pytorch.py
+++ b/ddlitlab2024/dataset/pytorch.py
@@ -79,30 +79,6 @@ def __init__(
         self.trajectory_stride = trajectory_stride
         self.num_joints = num_joints
 
-        # Define the naming and default ordering of the joints
-        self.joint_names = [
-            JointStates.head_pan.name,
-            JointStates.head_tilt.name,
-            JointStates.l_ankle_pitch.name,
-            JointStates.l_ankle_roll.name,
-            JointStates.l_elbow.name,
-            JointStates.l_hip_pitch.name,
-            JointStates.l_hip_roll.name,
-            JointStates.l_hip_yaw.name,
-            JointStates.l_knee.name,
-            JointStates.l_shoulder_pitch.name,
-            JointStates.l_shoulder_roll.name,
-            JointStates.r_ankle_pitch.name,
-            JointStates.r_ankle_roll.name,
-            JointStates.r_elbow.name,
-            JointStates.r_hip_pitch.name,
-            JointStates.r_hip_roll.name,
-            JointStates.r_hip_yaw.name,
-            JointStates.r_knee.name,
-            JointStates.r_shoulder_pitch.name,
-            JointStates.r_shoulder_roll.name,
-        ]
-
         # Print out metadata
         cursor = self.db_connection.cursor()
         cursor.execute("SELECT team_name, start_time, location, original_file FROM Recording")
@@ -143,7 +119,7 @@ def query_joint_data(
         )
 
         # Convert to numpy array, keep only the joint angle columns in alphabetical order
-        raw_joint_data = raw_joint_data[self.joint_names].to_numpy(dtype=np.float32)
+        raw_joint_data = raw_joint_data[JointStates.get_ordered_joint_names()].to_numpy(dtype=np.float32)
 
         assert raw_joint_data.shape[1] == self.num_joints, "The number of joints is not correct"
 
diff --git a/ddlitlab2024/ml/inference/ros.py b/ddlitlab2024/ml/inference/ros.py
new file mode 100644
index 0000000..b52406b
--- /dev/null
+++ b/ddlitlab2024/ml/inference/ros.py
@@ -0,0 +1,298 @@
+import time
+from threading import Lock
+from typing import Optional
+
+import cv2
+import numpy as np
+import rclpy
+import torch
+import torch.nn.functional as F  # noqa
+from bitbots_msgs.msg import JointCommand
+from bitbots_tf_buffer import Buffer
+from cv_bridge import CvBridge
+from diffusers.schedulers.scheduling_ddim import DDIMScheduler
+from ema_pytorch import EMA
+from game_controller_hl_interfaces.msg import GameState
+from profilehooks import profile
+from rclpy.callback_groups import MutuallyExclusiveCallbackGroup
+from rclpy.duration import Duration
+from rclpy.executors import MultiThreadedExecutor
+from rclpy.node import Node
+from rclpy.time import Time
+from sensor_msgs.msg import Image, JointState
+from trajectory_msgs.msg import JointTrajectory, JointTrajectoryPoint
+
+from ddlitlab2024 import DEFAULT_RESAMPLE_RATE_HZ
+from ddlitlab2024.dataset.models import JointStates
+from ddlitlab2024.dataset.pytorch import Normalizer
+from ddlitlab2024.ml.model import End2EndDiffusionTransformer
+from ddlitlab2024.ml.model.encoder.image import ImageEncoderType, SequenceEncoderType
+from ddlitlab2024.ml.model.encoder.imu import IMUEncoder
+
+# Check if CUDA is available and set the device
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+
+class Inference(Node):
+    def __init__(self, node_name, context):
+        super().__init__(node_name, context=context)
+        # Activate sim time
+        self.get_logger().info("Activate sim time")
+        self.set_parameters(
+            [rclpy.parameter.Parameter("use_sim_time", rclpy.Parameter.Type.BOOL, True)],
+        )
+
+        # Params
+        self.sample_rate = DEFAULT_RESAMPLE_RATE_HZ
+        hidden_dim = 256
+        self.action_context_length = 100
+        self.trajectory_prediction_length = 10
+        train_denoising_timesteps = 1000
+        self.inference_denosing_timesteps = 10
+        self.image_context_length = 10
+        self.imu_context_length = 100
+        self.joint_state_context_length = 100
+        self.num_joints = 20
+        checkpoint = (
+            "/home/florian/ddlitlab/ddlitlab_repo/ddlitlab2024/ml/training/"
+            "trajectory_transformer_model_500_epoch_xmas.pth"
+        )
+
+        # Subscribe to all the input topics
+        self.joint_state_sub = self.create_subscription(JointState, "/joint_states", self.joint_state_callback, 10)
+        self.img_sub = self.create_subscription(Image, "/camera/image_proc", self.img_callback, 10)
+        self.gamestate_sub = self.create_subscription(GameState, "/gamestate", self.gamestate_callback, 10)
+        self.motor_command_sub = self.create_subscription(
+            JointCommand, "/DynamixelController/command", self.motor_command_callback, 10
+        )
+
+        # Publisher for the output topic
+        # self.joint_state_pub = self.create_publisher(JointCommand, "/DynamixelController/command", 10)
+        self.trajectory_pub = self.create_publisher(JointTrajectory, "/traj", 10)
+
+        # Image embedding buffer
+        self.latest_image = None
+        self.image_embeddings = []
+
+        # IMU buffer
+        self.imu_data = []
+
+        # Joint state buffer
+        self.latest_joint_state: Optional[JointState] = None
+        self.joint_state_data = []
+
+        # Joint command buffer
+        self.latest_motor_command: Optional[JointCommand] = None
+        self.joint_command_data = []
+
+        # Gamestate
+        self.latest_game_state = None
+
+        # Add default values to the buffers
+        self.image_embeddings = [torch.randn(3, 480, 480)] * self.image_context_length
+        self.imu_data = [torch.randn(4)] * self.imu_context_length
+        self.joint_state_data = [
+            torch.randn(len(JointStates.get_ordered_joint_names()))
+        ] * self.joint_state_context_length
+        self.joint_command_data = [torch.randn(self.num_joints)] * self.action_context_length
+
+        self.data_lock = Lock()
+
+        # TF buffer to estimate imu similarly to the way we fixed the dataset
+        self.tf_buffer = Buffer(self, Duration(seconds=10))
+        self.cv_bridge = CvBridge()
+        self.rate = self.create_rate(self.sample_rate)
+
+        # Load model
+        self.get_logger().info("Load model")
+        self.model = End2EndDiffusionTransformer(
+            num_joints=self.num_joints,
+            hidden_dim=hidden_dim,
+            use_action_history=True,
+            num_action_history_encoder_layers=2,
+            max_action_context_length=self.action_context_length,
+            use_imu=True,
+            imu_orientation_embedding_method=IMUEncoder.OrientationEmbeddingMethod.QUATERNION,
+            num_imu_encoder_layers=2,
+            max_imu_context_length=self.imu_context_length,
+            use_joint_states=True,
+            joint_state_encoder_layers=2,
+            max_joint_state_context_length=self.joint_state_context_length,
+            use_images=True,
+            image_sequence_encoder_type=SequenceEncoderType.TRANSFORMER,
+            image_encoder_type=ImageEncoderType.RESNET18,
+            num_image_sequence_encoder_layers=1,
+            max_image_context_length=self.image_context_length,
+            num_decoder_layers=4,
+            trajectory_prediction_length=self.trajectory_prediction_length,
+        ).to(device)
+
+        self.og_model = self.model
+
+        self.normalizer = Normalizer(self.model.mean, self.model.std)
+        self.model = EMA(self.model)
+        self.model.load_state_dict(torch.load(checkpoint, weights_only=True))
+        self.model.eval()
+        print(self.normalizer.mean)
+
+        # Create diffusion noise scheduler
+        self.get_logger().info("Create diffusion noise scheduler")
+        self.scheduler = DDIMScheduler(beta_schedule="squaredcos_cap_v2", clip_sample=False)
+        self.scheduler.config["num_train_timesteps"] = train_denoising_timesteps
+        self.scheduler.set_timesteps(self.inference_denosing_timesteps)
+
+        # Create control timer to run inference at a fixed rate
+        interval = 1 / self.sample_rate * self.trajectory_prediction_length
+        # We want to run the inference in a separate thread to not block the callbacks, but we also want to make sure
+        # that the inference is not running multiple times in parallel
+        self.create_timer(interval, self.step, callback_group=MutuallyExclusiveCallbackGroup())
+        interval = 1 / self.sample_rate
+        self.create_timer(interval, self.update_buffers)
+
+    def joint_state_callback(self, msg: JointState):
+        self.latest_joint_state = msg
+
+    def img_callback(self, msg: Image):
+        self.latest_image = msg
+
+    def gamestate_callback(self, msg: GameState):
+        self.latest_game_state = msg
+
+    def motor_command_callback(self, msg: JointCommand):
+        self.latest_motor_command = msg
+
+    def update_buffers(self):
+        with self.data_lock:
+            # First we want to fill the buffers
+            if self.latest_joint_state is not None:
+                # Joint names are not in the correct order, so we need to reorder them
+                joint_state = torch.zeros(len(JointStates.get_ordered_joint_names()))
+                for i, joint_name in enumerate(JointStates.get_ordered_joint_names()):
+                    idx = self.latest_joint_state.name.index(joint_name)
+                    joint_state[i] = self.latest_joint_state.position[idx]
+                self.joint_state_data.append(joint_state)
+
+            if self.latest_motor_command is not None:
+                # Joint names are not in the correct order, so we need to reorder them
+                joint_state = torch.zeros(len(JointStates.get_ordered_joint_names()))
+                for i, joint_name in enumerate(JointStates.get_ordered_joint_names()):
+                    idx = self.latest_motor_command.joint_names.index(joint_name)
+                    joint_state[i] = self.latest_motor_command.positions[idx]
+                self.joint_command_data.append(joint_state)
+
+            if self.latest_image is not None:
+                # Here we don't just want to put the image in the buffer, but calculate the embedding first
+                # But for now the model dos not support the direct use of embeddings so we
+                # calculate them every timestep for the whole sequence.
+                # This is not efficient and should be changed in the future TODO
+
+                # Deserialize the image
+                img = self.cv_bridge.imgmsg_to_cv2(self.latest_image, desired_encoding="rgb8")
+
+                # Resize the image
+                img = cv2.resize(img, (480, 480))
+
+                # Make chw from hwc
+                img = np.moveaxis(img, -1, 0)
+
+                # Convert the image to a tensor
+                img = torch.tensor(img, dtype=torch.float32)
+
+                self.image_embeddings.append(img)
+
+            # Due to a bug in the recordings of the bit-bots we can not use the imu data directly,
+            # but instead need to derive it from the tf tree
+            imu_transform = self.tf_buffer.lookup_transform("base_footprint", "base_link", Time())
+
+            # Store imu data as np array in the form wxyz
+            self.imu_data.append(
+                torch.tensor(
+                    [
+                        imu_transform.transform.rotation.x,
+                        imu_transform.transform.rotation.y,
+                        imu_transform.transform.rotation.z,
+                        imu_transform.transform.rotation.w,
+                    ]
+                )
+            )
+
+            # Remove the oldest data from the buffers
+            self.joint_state_data = self.joint_state_data[-self.joint_state_context_length :]
+            self.image_embeddings = self.image_embeddings[-self.image_context_length :]
+            self.imu_data = self.imu_data[-self.imu_context_length :]
+            self.joint_command_data = self.joint_command_data[-self.action_context_length :]
+
+    @profile
+    def step(self):
+        self.get_logger().info("Step")
+
+        # Prepare the data for inference
+        with self.data_lock:
+            batch = {
+                "joint_state": (torch.stack(list(self.joint_state_data), dim=0).unsqueeze(0).to(device) + 3 * np.pi)
+                % (2 * np.pi),
+                "image_data": torch.stack(list(self.image_embeddings), dim=0).unsqueeze(0).to(device),
+                "rotation": torch.stack(list(self.imu_data), dim=0).unsqueeze(0).to(device),
+                "joint_command_history": (
+                    torch.stack(list(self.joint_command_data), dim=0).unsqueeze(0).to(device) + 3 * np.pi
+                )
+                % (2 * np.pi),  # torch.stack(list(self.joint_command_data), dim=0).unsqueeze(0).to(device),
+            }
+
+        # Perform the denoising process
+        trajectory = torch.randn(1, self.trajectory_prediction_length, self.num_joints).to(device)
+
+        start_ros_time = self.get_clock().now()
+
+        ## Perform the embedding of the conditioning
+        start = time.time()
+        embedded_input = self.og_model.encode_input_data(batch)
+        print("Time for embedding: ", time.time() - start)
+
+        # Denoise the trajectory
+        start = time.time()
+        self.scheduler.set_timesteps(self.inference_denosing_timesteps)
+        for t in self.scheduler.timesteps:
+            with torch.no_grad():
+                # Predict the noise residual
+                noise_pred = self.og_model.forward_with_context(
+                    embedded_input, trajectory, torch.tensor([t], device=device)
+                )
+
+                # Update the trajectory based on the predicted noise and the current step of the denoising process
+                trajectory = self.scheduler.step(noise_pred, t, trajectory).prev_sample
+
+        print("Time for forward: ", time.time() - start)
+
+        # Undo the normalization
+        trajectory = self.normalizer.denormalize(trajectory)
+
+        # Publish the trajectory
+        trajectory_msg = JointTrajectory()
+        trajectory_msg.header.stamp = Time.to_msg(start_ros_time)
+        trajectory_msg.joint_names = JointStates.get_ordered_joint_names()
+        trajectory_msg.points = []
+        for i in range(self.trajectory_prediction_length):
+            point = JointTrajectoryPoint()
+            point.positions = trajectory[0, i].cpu().numpy() - np.pi
+            point.time_from_start = Duration(nanoseconds=int(1e9 / self.sample_rate * i)).to_msg()
+            point.velocities = [3.0] * 2 + [-1.0] * (
+                len(JointStates.get_ordered_joint_names()) - 2
+            )  # TODO remove if interpolation is added
+            point.accelerations = [-1.0] * len(JointStates.get_ordered_joint_names())
+            point.effort = [-1.0] * len(JointStates.get_ordered_joint_names())
+            trajectory_msg.points.append(point)
+        self.trajectory_pub.publish(trajectory_msg)
+
+
+def main(args=None):
+    rclpy.init(args=args)
+    node = Inference("inference", None)
+    executor = MultiThreadedExecutor(num_threads=5)
+    executor.add_node(node)
+    executor.spin()
+    rclpy.shutdown()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/ddlitlab2024/ml/inference/trajectory_player.py b/ddlitlab2024/ml/inference/trajectory_player.py
new file mode 100644
index 0000000..df9f73c
--- /dev/null
+++ b/ddlitlab2024/ml/inference/trajectory_player.py
@@ -0,0 +1,90 @@
+from typing import Optional
+
+import rclpy
+import torch.nn.functional as F  # noqa
+from bitbots_msgs.msg import JointCommand
+from rclpy.callback_groups import MutuallyExclusiveCallbackGroup
+from rclpy.duration import Duration
+from rclpy.node import Node
+from rclpy.time import Time
+from trajectory_msgs.msg import JointTrajectory, JointTrajectoryPoint
+
+from ddlitlab2024 import DEFAULT_RESAMPLE_RATE_HZ
+
+
+class TrajectoryPlayer(Node):
+    def __init__(self, node_name, context):
+        super().__init__(node_name, context=context)
+        # Activate sim time
+        self.get_logger().info("Activate sim time")
+        self.set_parameters(
+            [rclpy.parameter.Parameter("use_sim_time", rclpy.Parameter.Type.BOOL, True)],
+        )
+
+        # Subscribers
+        self.trajectory_subscriber = self.create_subscription(
+            JointTrajectory,
+            "traj",
+            self.trajectory_callback,
+            10,
+            callback_group=MutuallyExclusiveCallbackGroup(),
+        )
+
+        self.joint_command_publisher = self.create_publisher(JointCommand, "DynamixelController/command", 10)
+
+        # Current trajectory
+        self.current_trajectory = None
+
+        self.create_timer(1 / DEFAULT_RESAMPLE_RATE_HZ, self.timer_callback)
+
+    def trajectory_callback(self, msg: JointTrajectory):
+        self.current_trajectory = msg
+
+    def timer_callback(self):
+        if self.current_trajectory is None:
+            self.get_logger().info("No trajectory available")
+            return
+
+        # Get the current time
+        current_time = self.get_clock().now()
+
+        # Find the current point based on the current time, the time the trajectory created and the time of the points
+        current_point: Optional[JointTrajectoryPoint] = None
+        for i, point in enumerate(self.current_trajectory.points):
+            time_of_point = Time.from_msg(self.current_trajectory.header.stamp) + Duration.from_msg(
+                point.time_from_start
+            )
+            if time_of_point < current_time:
+                current_point = point
+                a = i
+
+        print(
+            f"Using point {a} at time {time_of_point} as current point of the "
+            f"trajectory starting at {Time.from_msg(self.current_trajectory.header.stamp)}"
+        )
+
+        if current_point is None:
+            self.get_logger().info("Trajectory is in the future")
+            return
+
+        # Publish the current point
+        self.joint_command_publisher.publish(
+            JointCommand(
+                joint_names=self.current_trajectory.joint_names,
+                velocities=current_point.velocities,
+                accelerations=current_point.accelerations,
+                max_currents=current_point.effort,
+                positions=current_point.positions,
+            )
+        )
+
+
+def main(args=None):
+    rclpy.init(args=args)
+    node = TrajectoryPlayer("traj_player", None)
+    rclpy.spin(node)
+    rclpy.shutdown()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/ddlitlab2024/ml/model/misc.py b/ddlitlab2024/ml/model/misc.py
index 91a3162..dc213eb 100644
--- a/ddlitlab2024/ml/model/misc.py
+++ b/ddlitlab2024/ml/model/misc.py
@@ -48,12 +48,12 @@ def __init__(self, d_model, max_len):
         :param max_len: The maximum length of the input sequences.
         """
         super().__init__()
-        pe = torch.zeros(max_len, d_model)
+        self.register_buffer("pe", torch.zeros(1, max_len, d_model), persistent=False)
+
         position = torch.arange(0, max_len, dtype=torch.float).unsqueeze(1)
         div_term = torch.exp(torch.arange(0, d_model, 2).float() * (-np.log(10000.0) / d_model))
-        pe[:, 0::2] = torch.sin(position * div_term)
-        pe[:, 1::2] = torch.cos(position * div_term)
-        self.pe = pe.unsqueeze(0)
+        self.pe[0, :, 0::2] = torch.sin(position * div_term)
+        self.pe[0, :, 1::2] = torch.cos(position * div_term)
 
     def forward(self, x):
         """
@@ -62,4 +62,4 @@ def forward(self, x):
         :param x: The input tensor.
         :return: The input tensor with the positional encoding added.
         """
-        return x + self.pe[:, : x.size(1)].to(x.device)
+        return x + self.pe[:, : x.size(1)]
diff --git a/poetry.lock b/poetry.lock
index 133820d..9875943 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,9 +1,10 @@
-# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
+# This file is automatically @generated by Poetry and should not be changed by hand.
 
 [[package]]
 name = "alembic"
 version = "1.14.1"
 description = "A database migration tool for SQLAlchemy."
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -23,6 +24,7 @@ tz = ["backports.zoneinfo", "tzdata"]
 name = "certifi"
 version = "2024.12.14"
 description = "Python package for providing Mozilla's CA Bundle."
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -34,6 +36,7 @@ files = [
 name = "cffi"
 version = "1.17.1"
 description = "Foreign Function Interface for Python calling C code."
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -113,6 +116,7 @@ pycparser = "*"
 name = "charset-normalizer"
 version = "3.4.1"
 description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -214,6 +218,7 @@ files = [
 name = "colorama"
 version = "0.4.6"
 description = "Cross-platform colored terminal text."
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
@@ -225,6 +230,7 @@ files = [
 name = "contourpy"
 version = "1.3.1"
 description = "Python library for calculating contours of 2D quadrilateral grids"
+category = "main"
 optional = false
 python-versions = ">=3.10"
 files = [
@@ -298,6 +304,7 @@ test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist"
 name = "cycler"
 version = "0.12.1"
 description = "Composable style cycles"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -313,6 +320,7 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 name = "diffusers"
 version = "0.31.0"
 description = "State-of-the-art diffusion in PyTorch and JAX."
+category = "main"
 optional = false
 python-versions = ">=3.8.0"
 files = [
@@ -343,6 +351,7 @@ training = ["Jinja2", "accelerate (>=0.31.0)", "datasets", "peft (>=0.6.0)", "pr
 name = "docstring-parser"
 version = "0.16"
 description = "Parse Python docstrings in reST, Google and Numpydoc format"
+category = "main"
 optional = false
 python-versions = ">=3.6,<4.0"
 files = [
@@ -354,6 +363,7 @@ files = [
 name = "ema-pytorch"
 version = "0.7.7"
 description = "Easy way to keep track of exponential moving average version of your pytorch module"
+category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -368,6 +378,7 @@ torch = ">=2.0"
 name = "exceptiongroup"
 version = "1.2.2"
 description = "Backport of PEP 654 (exception groups)"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -382,6 +393,7 @@ test = ["pytest (>=6)"]
 name = "filelock"
 version = "3.17.0"
 description = "A platform independent file lock."
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
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 description = "Tools to manipulate font files"
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 ]
 
 [package.extras]
@@ -471,6 +484,7 @@ woff = ["brotli (>=1.0.1)", "brotlicffi (>=0.8.0)", "zopfli (>=0.1.4)"]
 name = "fsspec"
 version = "2024.12.0"
 description = "File-system specification"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -510,6 +524,7 @@ tqdm = ["tqdm"]
 name = "greenlet"
 version = "3.1.1"
 description = "Lightweight in-process concurrent programming"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -594,13 +609,14 @@ test = ["objgraph", "psutil"]
 
 [[package]]
 name = "huggingface-hub"
-version = "0.27.1"
+version = "0.28.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
+category = "main"
 optional = false
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -613,13 +629,13 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
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 inference = ["aiohttp"]
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 tensorflow = ["graphviz", "pydot", "tensorflow"]
 tensorflow-testing = ["keras (<3.0)", "tensorflow"]
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 name = "idna"
 version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
+category = "main"
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 python-versions = ">=3.6"
 files = [
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 name = "importlib-metadata"
 version = "8.6.1"
 description = "Read metadata from Python packages"
+category = "main"
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 python-versions = ">=3.9"
 files = [
@@ -667,6 +685,7 @@ type = ["pytest-mypy"]
 name = "iniconfig"
 version = "2.0.0"
 description = "brain-dead simple config-ini parsing"
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -678,6 +697,7 @@ files = [
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 version = "3.1.5"
 description = "A very fast and expressive template engine."
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -695,6 +715,7 @@ i18n = ["Babel (>=2.7)"]
 name = "kiwisolver"
 version = "1.4.8"
 description = "A fast implementation of the Cassowary constraint solver"
+category = "main"
 optional = false
 python-versions = ">=3.10"
 files = [
@@ -784,6 +805,7 @@ files = [
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 version = "1.2.2"
 description = "a modern parsing library"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
-docs = ["sphinx (>=1.6.0)", "sphinx-bootstrap-theme"]
+docs = ["sphinx (>=1.6.0)", "sphinx_bootstrap_theme"]
 flake8 = ["flake8"]
 tests = ["psutil", "pytest (!=3.3.0)", "pytest-cov"]
 
@@ -851,6 +869,7 @@ tests = ["psutil", "pytest (!=3.3.0)", "pytest-cov"]
 name = "mako"
 version = "1.3.8"
 description = "A super-fast templating language that borrows the best ideas from the existing templating languages."
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -870,6 +889,7 @@ testing = ["pytest"]
 name = "markdown-it-py"
 version = "3.0.0"
 description = "Python port of markdown-it. Markdown parsing, done right!"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -894,6 +914,7 @@ testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"]
 name = "markupsafe"
 version = "3.0.2"
 description = "Safely add untrusted strings to HTML/XML markup."
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -964,6 +985,7 @@ files = [
 name = "matplotlib"
 version = "3.10.0"
 description = "Python plotting package"
+category = "main"
 optional = false
 python-versions = ">=3.10"
 files = [
@@ -1021,6 +1043,7 @@ dev = ["meson-python (>=0.13.1,<0.17.0)", "pybind11 (>=2.13.2,!=2.13.3)", "setup
 name = "mcap"
 version = "1.2.2"
 description = "MCAP libraries for Python"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1036,6 +1059,7 @@ zstandard = "*"
 name = "mcap-ros2-support"
 version = "0.5.5"
 description = "ROS2 support for the Python MCAP library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1050,6 +1074,7 @@ mcap = ">=0.0.14"
 name = "mdurl"
 version = "0.1.2"
 description = "Markdown URL utilities"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1061,6 +1086,7 @@ files = [
 name = "mpmath"
 version = "1.3.0"
 description = "Python library for arbitrary-precision floating-point arithmetic"
+category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -1078,6 +1104,7 @@ tests = ["pytest (>=4.6)"]
 name = "mypy-extensions"
 version = "1.0.0"
 description = "Type system extensions for programs checked with the mypy type checker."
+category = "main"
 optional = false
 python-versions = ">=3.5"
 files = [
@@ -1089,6 +1116,7 @@ files = [
 name = "networkx"
 version = "3.4.2"
 description = "Python package for creating and manipulating graphs and networks"
+category = "main"
 optional = false
 python-versions = ">=3.10"
 files = [
@@ -1106,72 +1134,55 @@ test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
 
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+version = "1.26.4"
 description = "Fundamental package for array computing in Python"
+category = "main"
 optional = false
-python-versions = ">=3.10"
+python-versions = ">=3.9"
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+    {file = "numpy-1.26.4-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:7e50d0a0cc3189f9cb0aeb3a6a6af18c16f59f004b866cd2be1c14b36134a4a0"},
+    {file = "numpy-1.26.4.tar.gz", hash = "sha256:2a02aba9ed12e4ac4eb3ea9421c420301a0c6460d9830d74a9df87efa4912010"},
 ]
 
 [[package]]
 name = "nvidia-cublas-cu12"
 version = "12.4.5.8"
 description = "CUBLAS native runtime libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1184,6 +1195,7 @@ files = [
 name = "nvidia-cuda-cupti-cu12"
 version = "12.4.127"
 description = "CUDA profiling tools runtime libs."
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1196,6 +1208,7 @@ files = [
 name = "nvidia-cuda-nvrtc-cu12"
 version = "12.4.127"
 description = "NVRTC native runtime libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1208,6 +1221,7 @@ files = [
 name = "nvidia-cuda-runtime-cu12"
 version = "12.4.127"
 description = "CUDA Runtime native Libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1220,6 +1234,7 @@ files = [
 name = "nvidia-cudnn-cu12"
 version = "9.1.0.70"
 description = "cuDNN runtime libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1234,6 +1249,7 @@ nvidia-cublas-cu12 = "*"
 name = "nvidia-cufft-cu12"
 version = "11.2.1.3"
 description = "CUFFT native runtime libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1249,6 +1265,7 @@ nvidia-nvjitlink-cu12 = "*"
 name = "nvidia-curand-cu12"
 version = "10.3.5.147"
 description = "CURAND native runtime libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1261,6 +1278,7 @@ files = [
 name = "nvidia-cusolver-cu12"
 version = "11.6.1.9"
 description = "CUDA solver native runtime libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1278,6 +1296,7 @@ nvidia-nvjitlink-cu12 = "*"
 name = "nvidia-cusparse-cu12"
 version = "12.3.1.170"
 description = "CUSPARSE native runtime libraries"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1293,6 +1312,7 @@ nvidia-nvjitlink-cu12 = "*"
 name = "nvidia-nccl-cu12"
 version = "2.21.5"
 description = "NVIDIA Collective Communication Library (NCCL) Runtime"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1303,10 +1323,10 @@ files = [
 name = "nvidia-nvjitlink-cu12"
 version = "12.4.127"
 description = "Nvidia JIT LTO Library"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
-    {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_aarch64.whl", hash = "sha256:4abe7fef64914ccfa909bc2ba39739670ecc9e820c83ccc7a6ed414122599b83"},
     {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl", hash = "sha256:06b3b9b25bf3f8af351d664978ca26a16d2c5127dbd53c0497e28d1fb9611d57"},
     {file = "nvidia_nvjitlink_cu12-12.4.127-py3-none-win_amd64.whl", hash = "sha256:fd9020c501d27d135f983c6d3e244b197a7ccad769e34df53a42e276b0e25fa1"},
 ]
@@ -1315,6 +1335,7 @@ files = [
 name = "nvidia-nvtx-cu12"
 version = "12.4.127"
 description = "NVIDIA Tools Extension"
+category = "main"
 optional = false
 python-versions = ">=3"
 files = [
@@ -1327,6 +1348,7 @@ files = [
 name = "opencv-python"
 version = "4.11.0.86"
 description = "Wrapper package for OpenCV python bindings."
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -1341,9 +1363,12 @@ files = [
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
-    {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
-    {version = ">=1.23.5", markers = "python_version >= \"3.11\" and python_version < \"3.12\""},
+    {version = ">=1.21.2", markers = "python_version >= \"3.10\""},
+    {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\""},
+    {version = ">=1.19.3", markers = "python_version >= \"3.6\" and platform_system == \"Linux\" and platform_machine == \"aarch64\" or python_version >= \"3.9\""},
+    {version = ">=1.17.0", markers = "python_version >= \"3.7\""},
+    {version = ">=1.17.3", markers = "python_version >= \"3.8\""},
+    {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
     {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
 ]
 
@@ -1351,6 +1376,7 @@ numpy = [
 name = "packaging"
 version = "24.2"
 description = "Core utilities for Python packages"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1362,6 +1388,7 @@ files = [
 name = "pandas"
 version = "2.2.3"
 description = "Powerful data structures for data analysis, time series, and statistics"
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -1448,6 +1475,7 @@ xml = ["lxml (>=4.9.2)"]
 name = "pillow"
 version = "11.1.0"
 description = "Python Imaging Library (Fork)"
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -1536,6 +1564,7 @@ xmp = ["defusedxml"]
 name = "pluggy"
 version = "1.5.0"
 description = "plugin and hook calling mechanisms for python"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1551,6 +1580,7 @@ testing = ["pytest", "pytest-benchmark"]
 name = "profilehooks"
 version = "1.13.0"
 description = "Decorators for profiling/timing/tracing individual functions"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1562,6 +1592,7 @@ files = [
 name = "pycparser"
 version = "2.22"
 description = "C parser in Python"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1573,6 +1604,7 @@ files = [
 name = "pygments"
 version = "2.19.1"
 description = "Pygments is a syntax highlighting package written in Python."
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1587,6 +1619,7 @@ windows-terminal = ["colorama (>=0.4.6)"]
 name = "pyparsing"
 version = "3.2.1"
 description = "pyparsing module - Classes and methods to define and execute parsing grammars"
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -1601,6 +1634,7 @@ diagrams = ["jinja2", "railroad-diagrams"]
 name = "pytest"
 version = "8.3.4"
 description = "pytest: simple powerful testing with Python"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1623,6 +1657,7 @@ dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments
 name = "python-dateutil"
 version = "2.9.0.post0"
 description = "Extensions to the standard Python datetime module"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
@@ -1637,6 +1672,7 @@ six = ">=1.5"
 name = "pytz"
 version = "2024.2"
 description = "World timezone definitions, modern and historical"
+category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -1648,6 +1684,7 @@ files = [
 name = "pyyaml"
 version = "6.0.2"
 description = "YAML parser and emitter for Python"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1710,6 +1747,7 @@ files = [
 name = "regex"
 version = "2024.11.6"
 description = "Alternative regular expression module, to replace re."
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1813,6 +1851,7 @@ files = [
 name = "requests"
 version = "2.32.3"
 description = "Python HTTP for Humans."
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -1834,6 +1873,7 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "rich"
 version = "13.9.4"
 description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
+category = "main"
 optional = false
 python-versions = ">=3.8.0"
 files = [
@@ -1853,6 +1893,7 @@ jupyter = ["ipywidgets (>=7.5.1,<9)"]
 name = "ruff"
 version = "0.8.6"
 description = "An extremely fast Python linter and code formatter, written in Rust."
+category = "dev"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1880,6 +1921,7 @@ files = [
 name = "safetensors"
 version = "0.5.2"
 description = ""
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -1917,6 +1959,7 @@ torch = ["safetensors[numpy]", "torch (>=1.10)"]
 name = "scipy"
 version = "1.15.1"
 description = "Fundamental algorithms for scientific computing in Python"
+category = "main"
 optional = false
 python-versions = ">=3.10"
 files = [
@@ -1974,6 +2017,7 @@ test = ["Cython", "array-api-strict (>=2.0,<2.1.1)", "asv", "gmpy2", "hypothesis
 name = "setuptools"
 version = "75.8.0"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -1988,12 +2032,13 @@ cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "pyproject-hooks (!=1.1)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
 enabler = ["pytest-enabler (>=2.2)"]
 test = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "ini2toml[lite] (>=0.14)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.7.2)", "jaraco.test (>=5.5)", "packaging (>=24.2)", "pip (>=19.1)", "pyproject-hooks (!=1.1)", "pytest (>=6,!=8.1.*)", "pytest-home (>=0.5)", "pytest-perf", "pytest-subprocess", "pytest-timeout", "pytest-xdist (>=3)", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel (>=0.44.0)"]
-type = ["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (==1.14.*)", "pytest-mypy"]
+type = ["importlib_metadata (>=7.0.2)", "jaraco.develop (>=7.21)", "mypy (>=1.14.0,<1.15.0)", "pytest-mypy"]
 
 [[package]]
 name = "six"
 version = "1.17.0"
 description = "Python 2 and 3 compatibility utilities"
+category = "main"
 optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,>=2.7"
 files = [
@@ -2005,6 +2050,7 @@ files = [
 name = "sqlalchemy"
 version = "2.0.37"
 description = "Database Abstraction Library"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2100,6 +2146,7 @@ sqlcipher = ["sqlcipher3_binary"]
 name = "sympy"
 version = "1.13.1"
 description = "Computer algebra system (CAS) in Python"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2117,6 +2164,7 @@ dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
 name = "tabulate"
 version = "0.9.0"
 description = "Pretty-print tabular data"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2131,6 +2179,7 @@ widechars = ["wcwidth"]
 name = "tomli"
 version = "2.2.1"
 description = "A lil' TOML parser"
+category = "dev"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2172,6 +2221,7 @@ files = [
 name = "torch"
 version = "2.5.1"
 description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
+category = "main"
 optional = false
 python-versions = ">=3.8.0"
 files = [
@@ -2224,6 +2274,7 @@ optree = ["optree (>=0.12.0)"]
 name = "torchinfo"
 version = "1.8.0"
 description = "Model summary in PyTorch, based off of the original torchsummary."
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2235,6 +2286,7 @@ files = [
 name = "torchvision"
 version = "0.20.1"
 description = "image and video datasets and models for torch deep learning"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2258,7 +2310,7 @@ files = [
 
 [package.dependencies]
 numpy = "*"
-pillow = ">=5.3.0,<8.3.dev0 || >=8.4.dev0"
+pillow = ">=5.3.0,<8.3.0 || >=8.4.0"
 torch = "2.5.1"
 
 [package.extras]
@@ -2269,6 +2321,7 @@ scipy = ["scipy"]
 name = "tqdm"
 version = "4.67.1"
 description = "Fast, Extensible Progress Meter"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -2290,6 +2343,7 @@ telegram = ["requests"]
 name = "transforms3d"
 version = "0.4.2"
 description = "Functions for 3D coordinate transformations"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -2304,6 +2358,7 @@ numpy = ">=1.15"
 name = "triton"
 version = "3.1.0"
 description = "A language and compiler for custom Deep Learning operations"
+category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -2326,6 +2381,7 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 name = "typed-argument-parser"
 version = "1.10.1"
 description = "Typed Argument Parser"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2346,6 +2402,7 @@ dev-no-pydantic = ["flake8", "pytest", "pytest-cov"]
 name = "typing-extensions"
 version = "4.12.2"
 description = "Backported and Experimental Type Hints for Python 3.8+"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2357,6 +2414,7 @@ files = [
 name = "typing-inspect"
 version = "0.9.0"
 description = "Runtime inspection utilities for typing module."
+category = "main"
 optional = false
 python-versions = "*"
 files = [
@@ -2372,6 +2430,7 @@ typing-extensions = ">=3.7.4"
 name = "tzdata"
 version = "2025.1"
 description = "Provider of IANA time zone data"
+category = "main"
 optional = false
 python-versions = ">=2"
 files = [
@@ -2383,6 +2442,7 @@ files = [
 name = "urllib3"
 version = "2.3.0"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -2400,6 +2460,7 @@ zstd = ["zstandard (>=0.18.0)"]
 name = "zipp"
 version = "3.21.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
+category = "main"
 optional = false
 python-versions = ">=3.9"
 files = [
@@ -2419,6 +2480,7 @@ type = ["pytest-mypy"]
 name = "zstandard"
 version = "0.23.0"
 description = "Zstandard bindings for Python"
+category = "main"
 optional = false
 python-versions = ">=3.8"
 files = [
@@ -2530,4 +2592,4 @@ cffi = ["cffi (>=1.11)"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "11ad017d14ccb4eee4ec5ff1fa997a5bd2f32ee6360cb83f08a5e9600eb8c0da"
+content-hash = "3945c71fb142af13ea076bdc618d5d98fa22753c7ae2e727c70963c9bd58892b"
diff --git a/pyproject.toml b/pyproject.toml
index d5eaf08..4aaf117 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -15,7 +15,7 @@ python = "^3.10"
 diffusers = "^0.31.0"
 ema-pytorch = "^0.7.3"
 matplotlib = "^3.9.2"
-numpy = "^2.1.2"
+numpy = "^1.9.2"
 pandas = "^2.2.3"
 rich = "^13.9.3"
 sqlalchemy = "^2.0.36"