{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/get-yolo-layers","entry":"get_yolo_layers","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":5,"n_papers_ran":4,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":2,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":1,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":1},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2202.01811","paper":"/paper/objectseeker-certifiably-robust-object","title":"ObjectSeeker: Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking","date":"2022-02-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"inspire-group/ObjectSeeker","path":"yolor/models/models.py","file_url":"https://github.com/inspire-group/ObjectSeeker/blob/HEAD/yolor/models/models.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ad4cd570ddc892f3","mcp_get_code":{"code_sha256":"ad4cd570ddc892f3"}},{"arxiv_id":"2009.02967","paper":"/paper/stochastic-yolo-efficient-probabilistic","title":"Stochastic-YOLO: Efficient Probabilistic Object Detection under Dataset Shifts","date":"2020-09-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tjiagom/stochastic-yolo","path":"models.py","file_url":"https://github.com/tjiagom/stochastic-yolo/blob/HEAD/models.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"ec338718ed4c4fe1","mcp_get_code":{"code_sha256":"ec338718ed4c4fe1"}},{"arxiv_id":"2004.11757","paper":"/paper/ultra-fast-structure-aware-deep-lane","title":"Ultra Fast Structure-aware Deep Lane Detection","date":"2020-04-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":null,"path":"","file_url":null,"status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"code_sha256_prefix":"ec338718ed4c4fe1","mcp_get_code":{"code_sha256":"ec338718ed4c4fe1"}},{"arxiv_id":"2004.10934","paper":"/paper/yolov4-optimal-speed-and-accuracy-of-object","title":"YOLOv4: Optimal Speed and Accuracy of Object Detection","date":"2020-04-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"GuoQuanhao/YOLOv4-Paddle","path":"models/models.py","file_url":"https://github.com/GuoQuanhao/YOLOv4-Paddle/blob/HEAD/models/models.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ec338718ed4c4fe1","mcp_get_code":{"code_sha256":"ec338718ed4c4fe1"}},{"arxiv_id":"1804.02767","paper":"/paper/yolov3-an-incremental-improvement","title":"YOLOv3: An Incremental Improvement","date":"2018-04-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Raychou0830/Carplate","path":"models.py","file_url":"https://github.com/Raychou0830/Carplate/blob/HEAD/models.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"code_sha256_prefix":"ec338718ed4c4fe1","mcp_get_code":{"code_sha256":"ec338718ed4c4fe1"}}]}