ocsr/README.md

glyph-datasets / ocsr

Data artifacts for the OCSRGlyph model. Training images are not stored here: PubChem-format CSVs are rendered on the fly at train time (vendored EPAM Indigo), and the image-backed training sets carry SMILES + relative paths only, with the images re-fetched from the cited public sources. The one exception is the frozen self-contained eval parquet uspto_ocsr_benchmark.parquet, which embeds the 5,719 benchmark images (public-domain USPTO patent depictions) plus their complete labels so glyph ocsr eval runs with no reconstruction. Every other file is a benchmark label sidecar, training metadata (SMILES + optional relative image paths), or the training recipe.

Contents

File	Data rows	Kind	Provenance
uspto_ocsr_5719_complete.csv	5,719	Benchmark labels	Frozen, release-authoritative USPTO-OCSR-5719. See split below.
uspto_ocsr_5719_complete.csv.provenance.json	—	Sidecar	Per-source counts + recovered/unrecovered image ids for the benchmark.
uspto_ocsr_benchmark.parquet	5,719	Benchmark (self-contained)	Frozen images + complete labels; the single artifact glyph ocsr eval auto-downloads. See below.
uspto_ocsr_benchmark.parquet.provenance.json	—	Sidecar	Image source repo+SHA, label completion, row/null counts, and sha256.
adjacent_ring.csv	64,752	Training (this work)	Pure-logic adjacent-ring-stereo subset of PubChem-1M.
stereo_200k/train.csv	200,000	Training metadata	Stereo-200K (external). SMILES + file_path; images re-fetched.
stereo_200k/val.csv	2,000	Training metadata	Stereo-200K validation split.
stereo_200k_white/train.csv	200,000	Training metadata	White-cropped variant of Stereo-200K (this work's preprocessing).
stereo_200k_white/val.csv	2,000	Training metadata	White-cropped validation split.
ocsrglyph-recipe.json	—	Training recipe	The OCSRGlyph hyperparameter recipe.

Row counts are data rows (each CSV also has a 1-line header).

Frozen USPTO-OCSR-5719 benchmark

uspto_ocsr_5719_complete.csv is the exact benchmark behind the published headline numbers (A canonical 93.8, B chirality-kept 93.9, C graph 96.2, over the full 5,719 rows). It is frozen — use this copy verbatim rather than rebuilding, because a fresh rebuild against a newer MolScribe snapshot can drift the null-label recovery.

source_of_label split (recorded in the .provenance.json sidecar):

• hf_benchmark: 5,704 — public hheiden/USPTO_OCSR_benchmark labelled rows.
• molscribe_real: 13 — null labels recovered from MolScribe real/USPTO.csv (Qian et al., 2023).
• none_unrecovered: 2 — labels that could not be recovered.
• Total: 5,704 + 13 + 2 = 5,719; 5,711 RDKit-scoreable, 8 unscoreable.

Columns: image_id, smiles, source_of_label. Images are the public benchmark's patent depictions (referenced by image_id), not stored here.

Self-contained eval parquet

uspto_ocsr_benchmark.parquet is the single artifact glyph ocsr eval downloads: the 5,719 public benchmark images joined to the complete SMILES labels (columns id, image, smiles, selfies, inchi, mol, source_of_label; image bytes present for every row, zero null SMILES). It lets the eval score end-to-end with no local reconstruction, and its .provenance.json records the image source repo+SHA, the label completion, and the file sha256.

Credit. The benchmark images and the id/mol/selfies/inchi fields come verbatim from the public Hugging Face dataset hheiden/USPTO_OCSR_benchmark, whose depictions are drawn from public-domain USPTO patent documents — the origin of this OCSR benchmark. That upstream release labels 5,704 of the 5,719 images; the 15 remaining labels are completed here (13 recovered from the MolScribe real/USPTO.csv release, Qian et al. 2023; 2 left unrecovered), with source_of_label recording per-row provenance. Only the label completion and the join are this work; the images are not re-hosted beyond this frozen benchmark copy.

adjacent_ring (this work)

adjacent_ring.csv is the only "this work" OCSR training set: a pure-logic mined subset of PubChem-1M. A row is kept iff it has >=2 chiral centers with at least two of them adjacent atoms in the same ring, the SMILES length is in [50, 180], and RDKit can parse it. Scanning the 1,000,000-row PubChem-1M keeps 64,752 rows (6.48%). It is not a standalone dataset — whole rows are copied from PubChem-1M, so it overlaps that source 100% by construction. Columns: pubchem_cid, InChI, SMILES, num_atoms. Images render on the fly (Indigo).

(The mining rule is motivated by adjacent-ring-stereo "canary" patents, e.g. US07320972 / US07320974; the dataset name is adjacent_ring.)

Stereo-200K

stereo_200k/ and stereo_200k_white/ carry SMILES + relative file_path metadata only; the images themselves are the public Hugging Face dataset Robert-zwr/Stereo-200k (cite MolSight) and are re-fetched, not re-hosted here.

• stereo_200k/ — paths into the raw Stereo-200K tree (stereo/train/*.png). This is the set the training recipe and launcher reference (datasets/ocsr/stereo_200k).
• stereo_200k_white/ — the white-background + tight-crop preprocessing this work applies (background->white, largest-cluster crop). The SMILES targets are byte-identical to stereo_200k; only file_path differs (rewritten to the cropped tree). The white-crop preprocessing is this work; the base images are external.

Data mix (recipe)

The published OCSRGlyph run trains on 2,209,724 rows:

• 1,000,000 PubChem-1M + 680,220 USPTO-680K (public MolNexTR sources, CYF200127/MolNexTR), plus
• 2x 200,000 Stereo-200K + 2x 64,752 adjacent_ring.

The "x2" repeats are loader-level ConcatDataset weighting, not physical duplication. ocsrglyph-recipe.json records the model/optimization knobs (Swin-B/384 encoder, 6-layer transformer decoder, ImageNet-pretrained backbone, effective batch 256, cosine LR 4e-4, label smoothing 0.1, seed 42); it mirrors configs/ocsr/ocsrglyph-stereo-enriched.yaml in the code repo. The recipe's max_target_len is 480 (the design cap); the trainer caps decode length at 256.

Provenance summary

• External public, referenced / re-fetched (no image bytes stored here): PubChem-1M, USPTO-680K, the Stereo-200K base images, and the MolScribe recovery labels.
• This work (transformed metadata): adjacent_ring.csv (pure-logic mined subset of PubChem-1M), the Stereo-200K white-crop preprocessing (stereo_200k_white), the assembled 5,719 benchmark label composition, and the training recipe.
• Embedded copies: the frozen self-contained eval parquet uspto_ocsr_benchmark.parquet embeds the 5,719 hheiden/USPTO_OCSR_benchmark images (public-domain USPTO patent depictions) plus the complete labels, so glyph ocsr eval runs end-to-end with no reconstruction. It is the only artifact here that carries upstream image bytes.