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walzimmer / 3d-bat

Star 778

3D Bounding Box Annotation Tool (3D-BAT) Point cloud and Image Labeling

javascript multi-platform web < 10BC0 a data-hydro-click="{"event_type":"explore.click","payload":{"click_context":"REPOSITORY_CARD","click_target":"TOPIC","click_visual_representation":"TOPIC_TAG","actor_id":null,"record_id":9711,"originating_url":"https://github.com/topics/bounding-box","user_id":null}}" data-hydro-click-hmac="2cca3a9055ce38eabe2e85146dfffac5ba89925feae778ce79cc213e71c2a294" title="Topic: annotation" href="/topics/annotation" data-view-component="true" class="topic-tag topic-tag-link Link f6 mb-2">annotation tool interpolation detection point-cloud automatic autonomous-driving mechanical-turk 3d 2d active-learning pointcloud semi-automatic surround 3d-object-detection bounding-box multi-view
  • Updated Mar 7, 2024
  • TypeScript

kili-technology / kili-python-sdk

Star 231

Simplest and fastest image and text annotation tool.

annotation labeling semantic-segmentation semantic-annotation video-classification data-annotations image-labeling labeling-tool bounding-box text-labeling image-annotation-tool text-annotation-tool document-annotation-tool annotation-tool-online annotation-tool-offline computer-vision-annotation-tool image-texte-video-classification texte-video-classification
  • Updated Nov 24, 2025
  • Jupyter Notebook

YevgeniyEngineer / LiDAR-Processing-V2

Star 46

LiDAR processing ROS2. Segmentation: "Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process". Clustering: "Curved-Voxel Clustering for Accurate Segmentation of 3D LiDAR Point Clouds with Real-Time Performance".

docker c-plus-plus perception lidar cpp17 convex-hull velodyne depth-image principal-component-analysis clustering-algorithm ros2 kdtree lidar-point-cloud bounding-box polygonization rviz2 rotating-calipers lidar-segmentation
  • Updated Jul 20, 2024
  • C++

AgungHari / Development-of-YOLOV8-based-Autonomous-Wheelchair-for-Obstacle-Avoidance

Sponsor
Star 26

Detection is performed by combining two approaches: Yolo bounding box and pose landmarks, where both outputs are mapped into a 10x10 grid (made with OpenCV), which serves as a reference for the wheelchair to avoid obstacles. Commands are sent from the NUC to the ESP32, which then moves the motor.

pose-estimation bounding-box wheelchair-control mediapipe yolov8 grid10x10 kursiroda
  • Updated Apr 18, 2025
  • Python

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