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name: evaluation description: "Evaluate GroundingDINO on COCO-style data and diagnose zero-shot AP results." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

GroundingDINO Evaluation

Use this sub-skill when a user wants COCO zero-shot evaluation, bbox AP summaries, or evaluator API guidance for GroundingDINO. It covers dataset layout, config/checkpoint/device choices, category-caption postprocessing, and common AP failure modes.

Routes

• For a full COCO or COCO-style AP run, follow COCO evaluation and use the bundled helper at scripts/grounding_dino_coco_eval.py.
• For evaluator internals, prediction formats, and reusable APIs, read API reference.
• For failures such as missing COCO data, pycocotools import errors, CUDA/device mismatch, missing custom ops, or unexpectedly low AP, use troubleshooting.
• For single-image inference, prompts, token spans, or annotated outputs, route to inference.
• For pseudo-labeling folders or COCO export from detections, route to dataset annotation.

Required Inputs

• A GroundingDINO config file matching the checkpoint, such as the Swin-T OGC or Swin-B config distributed with the package/release.
• A matching checkpoint file already downloaded by the user; this sub-skill does not download weights.
• A COCO annotation JSON such as instances_val2017.json and an image directory containing the referenced file_name entries.
• A device choice: cuda, cuda:0, or cpu; CPU is useful for smoke tests but not benchmark-speed evaluation.

Fast Start

python sub-skills/evaluation/scripts/grounding_dino_coco_eval.py \
  -c configs/GroundingDINO_SwinT_OGC.py \
  -p weights/groundingdino_swint_ogc.pth \
  --anno_path datasets/coco/annotations/instances_val2017.json \
  --image_dir datasets/coco/val2017 \
  --device cuda \
  --num_select 300 \
  --num_workers 4

Expected output includes the constructed category prompt, progress messages, the IoU metric: bbox COCO summary table, and Final results: [...] with the bbox stats list. With the matching Swin-T OGC config, Swin-T OGC checkpoint, and official COCO val2017 data, the documented benchmark signal is about 48.5 bbox AP; mini-subsets and CPU smoke tests are validation checks, not benchmark evidence.