app.py

import gradio as gr

import os
import glob
import cv2
import numpy as np
import torch
from molscribe import MolScribe
from indigo import Indigo
from indigo.renderer import IndigoRenderer

from huggingface_hub import hf_hub_download

REPO_ID = "yujieq/MolScribe"
FILENAME = "swin_base_char_aux_1m.pth"
ckpt_path = hf_hub_download(REPO_ID, FILENAME)

device = torch.device('cpu')
model = MolScribe(ckpt_path, device)


def generate_mol_image(molblock):
 indigo = Indigo()
 render = IndigoRenderer(indigo)
 indigo.setOption('render-output-format', 'png')
 indigo.setOption('render-background-color', '1,1,1')
 indigo.setOption('render-stereo-style', 'none')
 indigo.setOption('render-label-mode', 'hetero')
 mol = indigo.loadMolecule(molblock)
 buf = render.renderToBuffer(mol)
 img = cv2.imdecode(np.asarray(bytearray(buf), dtype=np.uint8), 1)
 return img


def predict(image):
 prediction = model.predict_image(image)
 smiles = prediction['smiles']
 molfile = prediction['molfile']
 image = generate_mol_image(molfile)
 return image, smiles, molfile


iface = gr.Interface(
 predict,
 inputs=gr.Image(label="Upload molecular image", show_label=False).style(height=256),
 outputs=[
 gr.Image(label="Prediction").style(height=256),
 gr.Textbox(label="SMILES").style(show_copy_button=True),
 gr.Textbox(label="Molfile").style(show_copy_button=True),
 ],
 allow_flagging="auto",
 title="MolScribe",
 description="Convert a molecular image into SMILES and Molfile. (It typically takes 2-3 seconds to predict an "
 "image, but may take longer if the server is busy. To view the prediction better, copy-paste the "
 "Molfile to ChemDraw.) <br> " \
 "Paper: [_MolScribe: Robust Molecular Structure Recognition with Image-To-Graph Generation_](https://arxiv.org/abs/2205.14311) <br>" \
 "Code: https://github.com/thomas0809/MolScribe <br>" \
 "Authors: [Yujie Qian](mailto:[email protected]), Jiang Guo, Zhengkai Tu, Zhening Li, Connor W. Coley, Regina Barzilay. _MIT CSAIL_.",
 examples=sorted(glob.glob('examples/*.png')),
 examples_per_page=20,
)
iface.launch()