Update README.md

README.md

@@ -88,7 +88,7 @@ The eight numpy arrays store the spatial, temporal, and pose data for the trajec
 *   **`r_img.npy`**: A [T x 3] array containing the 2D ball tracking data per frame. The three columns represent the **`u`** (horizontal) coordinate, the **`v`** (vertical) coordinate, and a **visibility class**. The visibility class is binary, where 0 means the ball is out of frame/occluded, 1 means visible or hard to spot. The visibility class was directly extracke out of the TrackNet Dataset.
 *   **`2dPoseEstimation.npy`**: A [17 x 3] array containing the 2D human pose estimation of the hitting player when the racket touches the ball. The rows correspond to the 17 [COCO-WholeBody keypoints](https://arxiv.org/abs/2007.11858), and the columns represent the **`u`** coordinate, **`v`** coordinate, and a model confidence **`score`**. For whole serves, this pose is captured at the specific frame where the ball leaves the server's hand (or the first frame if the toss isn't visible).
 *   **`spin_class.npy`**: A 1D array of length [T] repeating the initial spin class for the length of the trajectory. The classes are categorized as **1 (topspin)** and **2 (backspin)** 
-*   **`new_trajectory_frame_idx.npy`**: An array of length [S] providing the exact frame indices (time steps) at which each new trajectory begins and the corresponding new spin value can be measured.
+*   **`start_serve.npy`**: Only relevant for serves: A scalar giving the image number referencing the Tracknet dataset that corresponds to the frame where the rackets touches the ball. (relevant fo)
 *   **`hits.npy`**: An array of length [H] providing the time stamps when the ball bounces on the floor. Normally, this H = 1 or H = 0, but if the ball is the final in the rally H can be greater 1.
 
 ## Download and Usage