Update README.md

README.md

@@ -21,38 +21,24 @@ The AD-Rallies dataset is a large-scale synthetic dataset generated using the Mu
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 ## Dataset Overview
 
-The dataset comprises  individual synthetic tennis trajectories. All physical kinematics, including the 3D positions, linear velocities, and angular velocities (spin), are captured at a high resolution of 500 frames per second (fps), corresponding to a time step of 0.002 seconds.
-The trajectories do not only comprise of the 3D trajectory information (position, velocity, ...) but also include camera parameters that define a camera's intrinsic and extrinsic camera matrix. The camera is always placed behind the baseline on the positive x-axis (see image).
+The dataset comprises of approxemately 3.2 Million synthetic tennis rallies. The rallies start with a ball toss, a serve and then up to 4 further basic strokes like (groundstroke, volley, lob, short and smash) can be added. All physical kinematics, including the 3D positions, linear velocities, and angular velocities (spin), are captured at a high resolution of 500 frames per second (fps), corresponding to a time step of 0.002 seconds.
 
-<img src="./camera_and court_origin.png" alt="Camera position in realtion to the world coordinate frame" style="width:50%; height:auto;" >
+The dataset is saved as a .tar file becuase it compromises out of 3.2 Million .npz files. The tar file has a size of 87 GB. 
+The npz file includes the position, velocity and angular velocity of the ball through the whole rally. 
 
-## Size
+The name if the npz files is like follows:
+toss_xxxxx_branch_yyy.npz or toss_xxxxx_branch_yyy_deadend.npz
 
-The dataset is saved as a .tar file becuase it compromises out of 187,200 individual folders. The tar file has a size of 17 GB. The unpacked dataset has a size of approx. 20 GB
-
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-
-# Folder Structure & Metadata
-Unlike datasets that use a separate JSON or CSV file for labels, the metadata for each trajectory is encoded directly into its folder path. The repository utilizes a four-tier nested folder structure categorized by the specific properties of the shot:
-
-    Base Stroke (Hit Type): The top-level folder defines the stroke. There are 7 options: groundstroke, lob, serve, short, smash, toss, or volley.
-    Direction of Flight: The second tier defines the trajectory's direction in raltion to the camera's position, organized into close_to_far and far_to_close subfolders. Close_to_far means that the ball is flying in the negative x-axis direction. Far_to_close means the ball flies in the positce x-axis direction. 
-    Status (In/Out): The third tier indicates whether the ball's first bounce landed validly inside the court (in) or outside the lines (out).
-    Trajectory ID: The final folder contains the isolated data for a single shot, numbered sequentially (e.g., trajectory_0000, trajectory_0001, ...).
-
-Example Path: groundstroke/close_to_far/in/trajectory_0000/
+Where xxxxx is the number of one of the 20000 tosses that were initially simulated and start the rally. Combined with a server this creates the stem for the rallies. For each stem rally upto 4 returns are added. These are numbered in increasing order as branch_yyy. The number of max rallies emerging out of one toss-serve combination is 160. 
+If  there is no feasable return found the rally is no longer stritched together (even though it has less than a total of 6 shots in the rally). This rally is then marked with "_deadend".
 
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 # Data Structures per Trajectory
-Inside each trajectory_xxxx folder, you will find exactly seven .npy files. These numpy arrays store the spatial, temporal, and camera data for that specific sequence:
+Inside each npz, you will find exactly seven .npy files. These numpy arrays store the spatial, temporal, and camera data for that specific sequence:
 
-    positions.npy: The 3D position of the ball (x, y, z) throughout the trajectory, recorded at a resolution of 0.002s.
+    positions.npy: The 3D position of the ball (x, y, z) throughout the rally, recorded at a resolution of 0.002s.
     velocities.npy: The linear velocity of the ball relative to the world coordinate system, recorded at a resolution of 0.002s.
     rotations.npy: The angular velocity (spin) of the ball in all 3 directions, recorded at a resolution of 0.002s.
-    times.npy: A 1D array containing the corresponding timestamps for the positions, velocities, and rotations arrays.
-    bounces.npy: Includes the exact timestamps of the bounces occurring during the trajectory, where t=0 represents the start of the trajectory.
-    Mint.npy: The intrinsic camera matrix.
-    Mext.npy: The extrinsic camera matrix.
 
 The position and velocity is defined in relation to the 3D world coordinate system, which is defined like follows:
 <img src="./3d_coordinate_system_in_field.png" alt="Coordinate system definition of 3D world coordinates" style="width:50%; height:auto;" >
@@ -60,8 +46,6 @@ The position and velocity is defined in relation to the 3D world coordinate syst
 The ball spin (rotations.npy) is defined in relation to the ball's local coordinate system. The direction of  which is defined as follows:
 <img src="./Screenshot 2026-04-20 194926.png" alt="Definition of the ball's local coordinate system" >
 
-Note on 2D Image Projections: To save space and reduce redundancy, this dataset does not include pre-calculated 2D image projections (u,v). Because both the intrinsic (Mint) and extrinsic (Mext) camera matrices are provided for every trajectory, users can easily calculate the 2D image projections themselves by multiplying the 3D world coordinates by the provided camera matrices.
-
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 # Download the Dataset