update collision task

README.md

@@ -35,11 +35,11 @@ The CathAction dataset is designed for the collision detection task, which invol
 
 The dataset is organized as follows:
 
-- **images/**: Contains images related to collision events, which serve as inputs for the collision detection model.
+- **images/**: Contains images related to collision and normal events.
   
-- **labels/**: Contains annotation files for each image. Each file provides information on bounding boxes, object classes, and collision occurrences in the corresponding image.
+- **labels/**: Contains annotation files for each image, detailing information on bounding boxes and object classes, including collision occurrences and the normal class for the corresponding image
 
-- **train_phantom.txt**: A text file listing paths to training images and labels for the "phantom" category in the collision detection task.
+- **train_phantom.txt**: A text file listing paths to training images and labels for the "phantom" data source in the collision detection task.
 
 - **valid_animal.txt**: A text file listing paths to validation images and labels for the "animal" source data.
 
@@ -52,4 +52,12 @@ Each `.txt` file contains a list of image and label paths for its respective cat
 1. **Training**: Use `train_phantom.txt` to load training data for the phantom category.
 2. **Validation**: Use `valid_animal.txt` and `valid_phantom.txt` for validating model performance on different data sources, specifically focusing on the 'animal' and 'phantom' data.
 
-This structure supports streamlined data loading and management for training, validating, and testing collision detection algorithms.
+This structure supports streamlined data loading and management for training, validating, and testing collision detection algorithms.
+
+For more information, please visit our [webpage](https://airvlab.github.io/cathaction/).
+
+For inquiries or assistance, please contact the authors at [this link](https://airvlab.github.io/cathaction/).
+
+Best regards,
+
+Authors