detect op• Data kinds: table × image2d → table
• Call: import fullseye as fs; fs.ledger.find_ncc_models(model, image, min_score=0.5, max_matches=10, min_distance=5) (to call the implementation directly, import shapematch; shapematch.find_ncc_models(model, image, min_score=0.5, max_matches=10, min_distance=5); from the registry, opsmv.get("find_ncc_models"))
• HALCON equivalent: find_ncc_models (the HALCON reference is a useful guide to its meaning and parameters)
• GPU: none (CPU reference implementation only)
Find one or more NCC models in one image.
> The detailed description below is the original text — the summary and the headings are translated.
model がモデルのリストなら全モデルを探し、各一致に model(リストの添字)を付けてスコアの順に並べ、min_distance より近い一致は強い方だけ残す。一致が無いと matches が空で num が 0 を返す(理由: 見つからないのは正常な結果)。空の入力(model のリストが 0 要素)は ValueError。
model が 1 つのときは min_distance を共通検索核へ渡す旧入口のまま。
• machine_vision_classics family guide
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• machine_vision_tour — py -3.11 examples/machine_vision_tour.py
table as input)map_image · rectify_to_world_plane · change_radial_distortion_image · run_bg_esti · give_bg_esti · update_bg_esti · classify_class_gmm · evaluate_class_gmm
detect)points_lepetit · create_ncc_model
*Provenance: shapematch.py — MV operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.