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---
dataset_info:
- config_name: pretrain_synthetic_7M
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dtype: image
- name: SMILES
dtype: string
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- config_name: valid
features:
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dtype: image
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dtype: string
splits:
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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.
* MolParser-Pretrain: More than 7.7M synthetic training data in `pretrain_synthetic_7M` subset;
* MolParser-SFT [WIP]: Nearly 400k samples for fine-tuning stage. (We have identified some annotation errors and are currently re-cleaning the data. Once completed, we will partially open-source it.)
* MolParser-Val: 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 Benchmark [WIP]: 20k molecule structure images cropped from real patents or paper `test_simple_10k`（ordinary）subset and `test_markush_10k`（markush）subset; (We have identified some annotation errors, we will update the version)
As the paper is still **under review**, this data is provided **anonymously**. More information will be provided after the paper has been accepted.
In the future, we will continue to re-clean this dataset, open-source more data, update model checkpoints, refresh the benchmark results, and release the training code.
[**Anonymous Demo: Click Here**](http://101.126.35.171:50008/) |