File size: 2,391 Bytes
cb0ccdd 464b486 d6065ea e350427 d6065ea e350427 de89b34 e350427 de89b34 e350427 de89b34 cb0ccdd e350427 cb0ccdd e350427 cb0ccdd 464b486 e350427 d6065ea e350427 de89b34 e350427 cb0ccdd e350427 66fc144 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
---
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
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 is accepted.
[**Anonymous Demo: Click Here**](http://180.184.38.121:50008/) |