groundingdino

X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.

Based on GroundingDino and SAM, use semantic strings to segment any element in an image. The comfyui version of sd-webui-segment-anything.

使用onnxruntime部署GroundingDINO开放世界目标检测，包含C++和Python两个版本的程序

juxtapose: Multi-Person Pose Tracking Inference SDK with RTMDet, YOLOv8, GDino, RTMPose (ONNX) & Trackers (ByteTrack & BotSORT) & Tapnet with custom ROIs + FastAPI GPU exe

Extract objects from images or video via text prompt

基于 React、C++20、SQLite、RAM 与 GroundingDINO 的自动图像标注平台，支持同步/异步任务和 COCO/YOLO 导出。

This project represents a GroundingDINO Inference (zero-shot object detection) procedure with both methods (CLI and Script). This implementation will help the reader to know the sequence of commands and exemplifying commands for running a quick zero-shot object detection. Additionally, the reader may get insight into code (script) execution.

Support batch inference of Grounding DINO. "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

Prompt based automatic annotation

language‑guided object detection that outputs a single pick target for robotic pick‑and‑place tasks

Run GroundingDINO as a local REST API using Docker. Easily send images and text prompts for object grounding.

Open vocabulary object detection using GroundingDINO with natural language prompts.

Language-guided semantic robot navigation in NVIDIA Isaac Sim (ROS 2): SLAM + Nav2 + GroundingDINO scene graph + a Qwen2.5-VL robot brain that turns natural-language commands into navigation goals.

Turns plain english commands into robot navigation via open-vocabulary object detection and LLM-driven replanning on failure.

VLM-assisted object detection, COCO dataset generation, and YOLO fine-tuning tools.

Open-vocabulary part detection + LLM reasoning for context-aware AR assembly instructions — GroundingDINO + Llama 3.2 + Unity JSON output

Set of completed codes created for the research program

A customizable pipeline for eye tracking in the wild via Grounded Segment Anything

Dorsal fin segmentation and matching with Grounded SAM and SIFT / Hu-moments