metadata

dataset_info:
  - config_name: pretrain_synthetic_7M
    features:
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: train
        num_bytes: 115375911760.028
        num_examples: 7720468
    download_size: 122046202421
    dataset_size: 115375911760.028
  - config_name: test_markush_10k
    features:
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: train
        num_bytes: 228019568
        num_examples: 10000
    download_size: 233407872
    dataset_size: 228019568
  - config_name: test_simple_10k
    features:
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: train
        num_bytes: 291640094
        num_examples: 10000
    download_size: 292074581
    dataset_size: 291640094
  - config_name: valid
    features:
      - name: image
        dtype: image
      - name: SMILES
        dtype: string
    splits:
      - name: train
        num_bytes: 13538058
        num_examples: 403
    download_size: 13451383
    dataset_size: 13538058
configs:
  - config_name: pretrain_synthetic_7M
    data_files:
      - split: train
        path: pretrain_synthetic_7M/train-*
  - config_name: valid
    data_files:
      - split: train
        path: valid/train-*
  - config_name: test_simple_10k
    data_files:
      - split: train
        path: test_simple_10k/train-*
  - config_name: test_markush_10k
    data_files:
      - split: train
        path: test_markush_10k/train-*
license: mit
tags:
  - chemistry

MolParser-7M

Anonymous Open Source now

This repo provids the training data and evaluation data for MolParser, proposed in paper “MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild“

MolParser-7M contains nearly 8 million paired image-SMILES data. It should be noted that the caption of image is our extended-SMILES format, which suggested in our paper.

Training Dataset: More than 7.7M training data in pretrain_synthetic_7M subset;
Validation Dataset: A small validation set carefully selected in-the-wild in valid subset. It can be used to quickly valid the model ability during the training process;
WildMol-20k: 20k molecule structure images cropped from real patents or paper test_simple_10k（ordinary）subset and test_markush_10k（markush）subset;

As the paper is still under review, this data is provided anonymously. More information will be provided after the paper has been accepted.

Anonymous Demo: Click Here