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- segmentation
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- segmentation
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# CathAction Dataset
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CathAction is large-scale dataset designed for advancing catheterization understanding. CathAction comprises annotated frames focused on catheterization understanding and collision detection, along with groundtruth masks dedicated to catheter and guidewire segmentation.
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Please fill out the [download form](https://airvlab.github.io/cathaction/docs/download/) and agree to our license prior to downloading the dataset.
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# Dataset Structure:
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## 1. Catheterization Action understanding
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The CathAction dataset encompasses annotated frames for catheterization action understanding task such as catheterization anticipation and action recognition.
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These are five classes: *advance catheter*, *retract catheter*, *advance guidewire*, *retract guidewire*, and *rotate*.
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### Annotation Files Structure
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The groundtruth CSV file containing 6 columns:
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| Column Name | Type | Example | Description |
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| ------------------- | ---------------------------- | ---------------- | --------------------------------------------------------------------------------------------------------------------- |
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| `video_id` | string | `video_1` | Video the segment is in |
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| `start_frame` | int | `430` | Start frame of the action |
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| `stop_frame` | int | `643` | End frame of the action |
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| `all_action_classes` | list of int (1 or more) | `[1]` | List of numeric IDs corresponding to all of the parsed Action' classes. |
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