Add task categories, project links and sample usage (#2)

- Add task categories, project links and sample usage (a7be20309b880d934d0788e94f2d358475411cb8)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -1,7 +1,8 @@
 ---
 license: apache-2.0
+task_categories:
+- object-detection
 tags:
-- arxiv:2605.15779
 - computer-vision
 - object-tracking
 - multi-camera
@@ -14,8 +15,11 @@ This dataset contains synchronized multi-UAV video footage and comprehensive tra
 
 It is designed for evaluating real-time multi-camera multi-vehicle tracking (MCMT) systems, focusing on solving trajectory fragmentation and maintaining global identity persistence across isolated UAV fields of view.
 
+- **Project Page:** [https://www.jye.me/ICUAS2026/](https://www.jye.me/ICUAS2026/)
+- **GitHub Repository:** [https://github.com/JYe9/multi-camera-multi-vehicle-tracking-system](https://github.com/JYe9/multi-camera-multi-vehicle-tracking-system)
+
 <p align="center">
-  <img src="assets/Pipeline.png" alt="Multi-Camera Multi-Vehicle Tracking Pipeline" width="80%"/>
+  <img src="https://huggingface.co/datasets/jye9/Multi-Camera-Multi-Vehicle-Tracking-System/resolve/main/assets/Pipeline.png" alt="Multi-Camera Multi-Vehicle Tracking Pipeline" width="80%"/>
 </p>
 
 ## Dataset Contents
@@ -27,9 +31,9 @@ Three synchronized 1-minute video clips captured from different UAV perspectives
 - `uav3_1min.mp4`
 
 <p align="center">
-  <img src="assets/uav1.jpg" alt="UAV1" width="32%"/>
-  <img src="assets/uav2.jpg" alt="UAV2" width="32%"/>
-  <img src="assets/uav3.jpg" alt="UAV3" width="32%"/>
+  <img src="https://huggingface.co/datasets/jye9/Multi-Camera-Multi-Vehicle-Tracking-System/resolve/main/assets/uav1.jpg" alt="UAV1" width="32%"/>
+  <img src="https://huggingface.co/datasets/jye9/Multi-Camera-Multi-Vehicle-Tracking-System/resolve/main/assets/uav2.jpg" alt="UAV2" width="32%"/>
+  <img src="https://huggingface.co/datasets/jye9/Multi-Camera-Multi-Vehicle-Tracking-System/resolve/main/assets/uav3.jpg" alt="UAV3" width="32%"/>
 <br/>
 <em>Example: Consistent global tracking (e.g., the red car with ID 70) across overlapping UAV fields of view.</em>
 </p>
@@ -40,16 +44,29 @@ The dataset includes structured CSV files with rich metadata generated by our tr
 **Base Schema:**
 ```text
 frame_index, x_min, y_min, x_max, y_max, class_id, confidence, tracker_id, global_id, camera_id, speed, status
-
 ```
 
 *Note: Speed is estimated in km/h via pixel-to-meter scaling. Status tracks active/new_entry/exiting states.*
 
-## Tracking Pipeline Code
-
-The full production-ready pipeline (utilizing YOLO11, ByteTrack, and our Topology-based Spatiotemporal Handover mechanism) used to process these videos is open-source.
-
-🔗 **[View Source Code on GitHub](https://www.google.com/search?q=https://github.com/JYe9/multi-camera-multi-vehicle-tracking-system)**
+## Sample Usage
+
+After cloning the [GitHub repository](https://github.com/JYe9/multi-camera-multi-vehicle-tracking-system) and installing the requirements, you can run the pipeline with the following command:
+
+```bash
+python main.py \
+  --source_video_path_uav1 videos/uav1_1min.mp4 \
+  --target_video_path_uav1 output_videos/1mins_UAV1_output.mp4 \
+  --target_csv_path_uav1 csv/1mins_UAV1.csv \
+  --source_video_path_uav2 videos/uav2_1min.mp4 \
+  --target_video_path_uav2 output_videos/1mins_UAV2_output.mp4 \
+  --target_csv_path_uav2 csv/1mins_UAV2.csv \
+  --source_video_path_uav3 videos/uav3_1min.mp4 \
+  --target_video_path_uav3 output_videos/1mins_UAV3_output.mp4 \
+  --target_csv_path_uav3 csv/1mins_UAV3.csv \
+  --model_path models_zoo/3UAVs.pt \
+  --confidence_threshold 0.5 \
+  --iou_threshold 0.5
+```
 
 ## Citation
 
@@ -64,5 +81,4 @@ If you find this dataset or our framework useful in your research, please cite o
       archivePrefix={arXiv},
       primaryClass={cs.CV}
 }
-
 ```