update for collision task

README.md

@@ -30,3 +30,26 @@ The groundtruth CSV file containing 6 columns:
 | `stop_frame`        | int                          | `643`          | End frame of the action                                                        |
 | `all_action_classes` | list of int    (1 or more)   | `[1]`           | List of numeric IDs corresponding to all of the parsed Action' classes.                             |
 
+## 2. Collision Detection
+The CathAction dataset is designed for the collision detection task, which involves identifying whether the tip of the catheter or guidewire comes into contact with the blood vessel wall.
+
+The dataset is organized as follows:
+
+- **images/**: Contains images related to collision events, which serve as inputs for the collision detection model.
+  
+- **labels/**: Contains annotation files for each image. Each file provides information on bounding boxes, object classes, and collision occurrences in 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.
+
+- **valid_animal.txt**: A text file listing paths to validation images and labels for the "animal" source data.
+
+- **valid_phantom.txt**: A text file listing paths to validation images and labels for the "phantom" source data.
+
+Each `.txt` file contains a list of image and label paths for its respective category and split (train/validation), enabling easy access and organization for model training and evaluation.
+
+### Usage
+
+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.