Update README.md

README.md

@@ -1,3 +1,58 @@
 ---
 license: cc-by-4.0
+task_categories:
+- object-detection
+- keypoint-detection
+- image-to-3d
+language:
+- en
+pretty_name: Spacecraft Detection Keypoint and Pose Dataset
+tags:
+- spacecraft
+- pose-estimation
+- satellite
+- computer-vision
+- 6dof
 ---
+
+# Dataset Card: SDKP (Spacecraft Detection, Keypoint, and Pose Dataset)
+
+## Dataset Description
+
+- **Homepage:** [Add project homepage or paper link here]
+- **License:** Creative Commons Attribution 4.0 International (CC BY 4.0)
+
+### Dataset Summary
+
+The SDKP (Spacecraft Detection, Keypoint, and Pose) dataset is a comprehensive benchmark designed to advance spacecraft perception under monocular imaging conditions. It contains **24,000** high-quality RGB images, each accompanied by rich ground-truth annotations including 2D semantic keypoints, bounding boxes, and full 6-DoF poses. The data is split into three standardized subsets—20,000 for training, 2,000 for validation, and 2,000 for testing—ensuring consistent evaluation protocols. Organized in a COCO-compatible format, the dataset includes camera intrinsic parameters and a 3D keypoint template defining all semantic landmarks in the spacecraft body frame. This resource targets three core computer vision tasks: object detection, keypoint localization, and pose estimation, providing a unified platform for developing and comparing algorithms in spaceborne applications.
+
+## Dataset Structure
+
+### Data Instance
+
+The dataset follows a COCO-compatible format. A typical data instance contains the following fields:
+
+- **Image:** RGB image containing the spacecraft.
+- **Annotations:**
+  - `bbox`: Object detection bounding box.
+  - `keypoints`: Predefined 2D semantic keypoint coordinates with visibility flags.
+  - `pose`: Full 6-DoF pose (rotation matrix and translation vector).
+- **Metadata:**
+  - `camera_intrinsics`: Camera intrinsic parameter matrix.
+  - `keypoint_template_3d`: 3D template of all semantic keypoints in the spacecraft body frame.
+
+### Data Splits
+
+| Split Name | Number of Images |
+| :--- | :--- |
+| **Training** | 20,000 |
+| **Validation** | 2,000 |
+| **Test** | 2,000 |
+
+## Supported Tasks
+
+This dataset is designed for three core computer vision tasks, providing a unified platform for algorithm development and evaluation:
+
+1.  **Object Detection:** Localize and identify spacecraft in images.
+2.  **Keypoint Localization:** Precisely predict 2D pixel coordinates of predefined semantic keypoints on the spacecraft.
+3.  **Pose Estimation:** Recover the 6-DoF pose of the spacecraft relative to the camera from a single RGB image.