FTIR-Deep Learning - FTIR Deep Learning With Python

Overview

CANDIY-spectrum

Human analyis of chemical spectra such as Mass Spectra (MS), Infra-Red Specta (FTIR), and Nuclear Magnetic Resonance is both time consuming and potentially inaccurate. This project aims to develop a set of methodologies incorporating these spectra for the prediction of chemical functional groups and structures.

Scraping

Manual Scraping

IR and MS spectra were downloaded from NIST website. https://webbook.nist.gov/chemistry/. Scraping can be done through replacing the correct CAS number in the placeholder. https://webbook.nist.gov/cgi/cbook.cgi?ID="insert_cas"&Units=SI and downloading the required spectra.

(Or)

Automatic Scraping

Download all the species name available in NIST from this link https://webbook.nist.gov/chemistry/download/. Change path of cas_list to where the species name file is stored.

python scrap.py --save_dir='./data/' --cas_list='species.txt' --scrap_IR=true --scrap_MS=true --scrap_InChi=true

Prepare dataset

Parse all jdx files of IR and Mass spectra to standardize and store in a csv format. Also, parse inchi.txt to create target csv indicating presence of functional groups

python prepare_load_dataset.py --data_dir='./data/' --cas_list='species.txt'

Train the model

Run Spectra_Train.ipynb to train the model.

Owner
Wei Mei
Wei Mei
Deep Learning Package based on TensorFlow

White-Box-Layer is a Python module for deep learning built on top of TensorFlow and is distributed under the MIT license. The project was started in M

YeongHyeon Park 7 Dec 27, 2021
Sionna: An Open-Source Library for Next-Generation Physical Layer Research

Sionna: An Open-Source Library for Next-Generation Physical Layer Research Sionna™ is an open-source Python library for link-level simulations of digi

NVIDIA Research Projects 313 Dec 22, 2022
"Domain Adaptive Semantic Segmentation without Source Data" (ACM MM 2021)

LDBE Pytorch implementation for two papers (the paper will be released soon): "Domain Adaptive Semantic Segmentation without Source Data", ACM MM2021.

benfour 16 Sep 28, 2022
MEND: Model Editing Networks using Gradient Decomposition

MEND: Model Editing Networks using Gradient Decomposition Setup Environment This codebase uses Python 3.7.9. Other versions may work as well. Create a

Eric Mitchell 141 Dec 02, 2022
Implementation of ToeplitzLDA for spatiotemporal stationary time series data.

Code for the ToeplitzLDA classifier proposed in here. The classifier conforms sklearn and can be used as a drop-in replacement for other LDA classifiers. For in-depth usage refer to the learning from

Jan Sosulski 5 Nov 07, 2022
🏅 Top 5% in 제2회 연구개발특구 인공지능 경진대회 AI SPARK 챌린지

AI_SPARK_CHALLENG_Object_Detection 제2회 연구개발특구 인공지능 경진대회 AI SPARK 챌린지 🏅 Top 5% in mAP(0.75) (443명 중 13등, mAP: 0.98116) 대회 설명 Edge 환경에서의 가축 Object Dete

3 Sep 19, 2022
PyTorch implementation of DirectCLR from paper Understanding Dimensional Collapse in Contrastive Self-supervised Learning

DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It

Meta Research 49 Dec 21, 2022
Resources complimenting the Machine Learning Course led in the Faculty of mathematics and informatics part of Sofia University.

Machine Learning and Data Mining, Summer 2021-2022 How to learn data science and machine learning? Programming. Learn Python. Basic Statistics. Take a

Simeon Hristov 8 Oct 04, 2022
Finetuning Pipeline

KLUE Baseline Korean(한국어) KLUE-baseline contains the baseline code for the Korean Language Understanding Evaluation (KLUE) benchmark. See our paper fo

74 Dec 13, 2022
Official repository for: Continuous Control With Ensemble DeepDeterministic Policy Gradients

Continuous Control With Ensemble Deep Deterministic Policy Gradients This repository is the official implementation of Continuous Control With Ensembl

4 Dec 06, 2021
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels

ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D

298 Dec 26, 2022
a baseline to practice

ccks2021_track3_baseline a baseline to practice 路径可能会有问题,自己改改 torch==1.7.1 pyhton==3.7.1 transformers==4.7.0 cuda==11.0 this is a baseline, you can fi

45 Nov 23, 2022
Neural network pruning for finding a sparse computational model for controlling a biological motor task.

MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo

Olivia Thomas 0 Dec 14, 2022
Convert weight file.pth to weight file.blob

CONVERT YOUR MODEL TO IR FORMAT INSTALLATION OpenVino Toolkit Download openvinotoolkit 2021.3 version : Link Instruction of installation : Link Pytorc

Tran Anh Tuan 3 Nov 18, 2021
BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构

BaseCls BaseCls 是一个基于 MegEngine 的预训练模型库,帮助大家挑选或训练出更适合自己科研或者业务的模型结构。 文档地址:https://basecls.readthedocs.io 安装 安装环境 BaseCls 需要 Python = 3.6。 BaseCls 依赖 M

MEGVII Research 28 Dec 23, 2022
PyTorch implementation of the Deep SLDA method from our CVPRW-2020 paper "Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis"

Lifelong Machine Learning with Deep Streaming Linear Discriminant Analysis This is a PyTorch implementation of the Deep Streaming Linear Discriminant

Tyler Hayes 41 Dec 25, 2022
Image-generation-baseline - MUGE Text To Image Generation Baseline

MUGE Text To Image Generation Baseline Requirements and Installation More detail

23 Oct 17, 2022
Implementation of ReSeg using PyTorch

Implementation of ReSeg using PyTorch ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation Pascal-Part Annotations Pascal VOC 2010

Onur Kaplan 46 Nov 23, 2022
Storchastic is a PyTorch library for stochastic gradient estimation in Deep Learning

Storchastic is a PyTorch library for stochastic gradient estimation in Deep Learning

Emile van Krieken 140 Dec 30, 2022
EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation

EFENet EFENet: Reference-based Video Super-Resolution with Enhanced Flow Estimation Code is a bit messy now. I woud clean up soon. For training the EF

Yaping Zhao 19 Nov 05, 2022