---

name: inference description: "Use GroundingDINO for single-image open-vocabulary detection, Python inference APIs, token spans, annotation, device selection, and output interpretation." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

GroundingDINO Inference

Use this sub-skill when a user needs single-image GroundingDINO inference with text prompts, class lists, token spans, annotated output images, or Python API integration.

Use This For

• Loading a GroundingDINO config/checkpoint and one image for open-vocabulary object detection.
• Choosing between groundingdino.util.inference functions and the Model wrapper API.
• Building prompts from free-form captions or class lists such as cat . dog . person ..
• Using token spans to target exact phrases inside a sentence prompt.
• Interpreting normalized cxcywh boxes, pixel xyxy annotations, logits/confidence, and phrases.
• Running the bundled CLI helper in scripts/grounding_dino_infer.py with explicit input validation.

Route Elsewhere

• COCO AP and benchmark evaluation: use ../evaluation/.
• Folder pseudo-label export or COCO-format dataset creation: use ../dataset-annotation/.
• Gradio, Hugging Face demo, Grounded-SAM, GLIGEN, or image-editing pipelines: use ../integrations/.
• Training or fine-tuning: treat as an unsupported gap because GroundingDINO training code is not released in this repo skill.

Quick Start

Prefer the bundled helper for one-off runs because it validates config, checkpoint, image, token spans, thresholds, and device before loading the model:

python sub-skills/inference/scripts/grounding_dino_infer.py \
  --config-file /path/to/GroundingDINO_SwinT_OGC.py \
  --checkpoint-path /path/to/groundingdino_swint_ogc.pth \
  --image-path /path/to/image.jpg \
  --text-prompt "chair . person . dog ." \
  --output-dir outputs/grounding-dino \
  --box-threshold 0.35 \
  --text-threshold 0.25 \
  --device cuda \
  --json-output

For CPU-only checks, add --cpu-only. For class-list prompts, use --classes cat dog "traffic light" instead of --text-prompt. For span-targeted phrases, use --text-prompt plus --token-spans; see references/token-spans.md.

References

• references/api-reference.md: function signatures, wrapper API, inputs, outputs, and box formats.
• references/workflows.md: CLI helper recipes, Python API recipes, validation commands, and output interpretation.
• references/token-spans.md: token span schema, offset validation, examples, and failure signals.
• references/troubleshooting.md: missing files, CPU/CUDA, _C custom op errors, no detections, and malformed prompts/spans.