README.md

metadata

language:
  - en
license: other
license_name: mixed-see-sources
task_categories:
  - image-to-text
tags:
  - chemistry
  - cheminformatics
  - ocsr
  - optical-chemical-structure-recognition
  - molecule-recognition
  - smiles
  - benchmark
pretty_name: OCSR Benchmarks
size_categories:
  - 10K<n<100K
configs:
  - config_name: ACS
    data_files:
      - split: test
        path: ACS/test-*
  - config_name: CLEF
    data_files:
      - split: test
        path: CLEF/test-*
  - config_name: ChemDraw
    data_files:
      - split: test
        path: ChemDraw/test-*
  - config_name: Indigo
    data_files:
      - split: test
        path: Indigo/test-*
  - config_name: JPO
    data_files:
      - split: test
        path: JPO/test-*
  - config_name: Staker
    data_files:
      - split: test
        path: Staker/test-*
  - config_name: UOB
    data_files:
      - split: test
        path: UOB/test-*
  - config_name: USPTO
    data_files:
      - split: test
        path: USPTO/test-*
  - config_name: USPTO-10K
    data_files:
      - split: test
        path: USPTO-10K/test-*
  - config_name: WildMol-10K
    data_files:
      - split: test
        path: WildMol-10K/test-*
dataset_info:
  - config_name: ACS
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 5001836
        num_examples: 331
    download_size: 5006693
    dataset_size: 5001836
  - config_name: CLEF
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 3308074
        num_examples: 992
    download_size: 3295643
    dataset_size: 3308074
  - config_name: ChemDraw
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 28724502
        num_examples: 5719
    download_size: 28929307
    dataset_size: 28724502
  - config_name: Indigo
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 224451958
        num_examples: 5719
    download_size: 226875357
    dataset_size: 224451958
  - config_name: JPO
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 2862316
        num_examples: 449
    download_size: 2860290
    dataset_size: 2862316
  - config_name: Staker
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 143142981
        num_examples: 50000
    download_size: 143167707
    dataset_size: 143142981
  - config_name: UOB
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 19040066
        num_examples: 5740
    download_size: 19037801
    dataset_size: 19040066
  - config_name: USPTO
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 20247285
        num_examples: 5719
    download_size: 20281040
    dataset_size: 20247285
  - config_name: USPTO-10K
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 59935636
        num_examples: 9999
    download_size: 59096324
    dataset_size: 59935636
  - config_name: WildMol-10K
    features:
      - name: image_id
        dtype: string
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: test
        num_bytes: 214403509
        num_examples: 9889
    download_size: 212929337
    dataset_size: 214403509

OCSR Benchmarks

A collection of ten benchmark datasets for Optical Chemical Structure Recognition (OCSR) — the task of converting chemical structure diagram images into machine-readable SMILES strings.

These benchmarks were used to evaluate the COMO model (Closed-Loop Optical Molecule Recognition).

Subsets

Config	Split	Size	Domain
CLEF	test	992	Real
JPO	test	449	Real
UOB	test	5,740	Real
USPTO	test	5719	Real
USPTO-10K	test	9,999	Real
Staker	test	50,000	Real
ACS	test	331	Real
WildMol-10K	test	9,889	Real
Indigo	test	5,719	Synthetic
ChemDraw	test	5,719	Synthetic

Schema

Each sample has three fields:

Field	Type	Description
image_id	string	Original identifier for the sample
image	Image	PNG image of the chemical structure diagram
SMILES	string	Ground-truth SMILES string

Usage

from datasets import load_dataset

# Load a single benchmark
ds = load_dataset("Keylab/OCSR-Benchmarks", name="USPTO", split="test")
sample = ds[0]
sample["image"].show()   # PIL Image
print(sample["SMILES"])

# Iterate over all benchmarks
for config in ["CLEF", "JPO", "UOB", "USPTO", "USPTO-10K",
               "Staker", "ACS", "WildMol-10K", "Indigo", "ChemDraw"]:
    ds = load_dataset("Keylab/OCSR-Benchmarks", name=config, split="test")
    print(f"{config}: {len(ds)} samples")

Bulk Download

Pre-packaged .tar.gz archives (images + CSV) are also available in the COMO model repository for direct download without the datasets library.

License

These benchmarks are collected from existing public OCSR datasets. Please refer to the original sources for attribution and applicable terms:

Dataset	Source
USPTO, CLEF, JPO, UOB, Staker	Rajan et al., 2020, Xiong et al., 2023
Indigo, ChemDraw, ACS, Staker	Qian et al., 2023
USPTO-10K	Morin et al., 2023
WildMol-10K	Fang et al., 2025

Citation

If you use these benchmarks, please cite the COMO paper and the original benchmark sources:

@article{lyu2026closed,
  title={COMO: Closed-Loop Optical Molecule Recognition with Minimum Risk Training},
  author={Lyu, Zhuoqi and Ke, Qing},
  journal={arXiv preprint arXiv:2604.23546},
  year={2026}
}