An open-source project for applying deep learning to medical scenarios

Overview

Auto Vaidya

An open source solution for creating end-end web app for employing the power of deep learning in various clinical scenarios like implant detection, pneumonia detection, brain mri segmentation etc.

Suggestions for PR:

  • Please give your PR for the test branch unless requested otherwise by the project maintainer
  • Name your PR appropiately
  • Ensure that you had already raised an issue for this PR and the project maintainer had approved and assigned you
  • In the PR description, typically the following are expected:
    • Dataset Used:
    • Dataset Size:
    • Dataset Source:
    • Link to Colab Notebook: Please ensure you give access for view to anyone with link
    • Your Exploratory Data Analysis [Snapshots of the relevant ones and your inference from that]
    • Any Pre-Processing methods used. [Elaborate on them]
    • Your framework to train
    • Different methods used for training
    • Test/Train Split
    • Results: Please do not simply state test accuracy. Other perfomance metrics like F1 score,etc are expected
    • ** Draw a table to show the comparitive analysis of the performance of the different methods you used
    • Conclusion: Which method you think is best and why?
  • A copy of the notebook used for your training is expected inside the notebooks/ directory.
  • Please name the notebook as name_of_the_problem_your_github_username
  • The model files are expected to be inside a models\name_of_your_problem\ directory
  • If you are using TensorFlow 2.0, please give both the h5 as well as saved_model file
  • Once your PR, gets approved uptil this, proceed with a follow up pr to integrate it inside the streamlit app. Refer this if you are unaware of how to use streamlit and host it
  • For the streamlit app, it would be a good practice if you define the function for classification/prediction/regression inside a separate python file say your_problem_name.py and import it inside app.py ( Believe me this would save a lot of time otherwise wasted in debugging)
  • For the second PR, you are expected to do the above changes and provide screenshots/a small clip of the working model of the app after integrating your model from the previous PR
  • For the second PR, it should be one the test branch only, later the project maintainers will merge it with the master branch for a stable release
  • For PRs, related to frontend please give it to the frontend branch
  • Once accepted, give a follow up PR to the test branch to render your html,css files for a page using streamlit
  • As stated above you are expected to give screenshots, descriptions and other details for the PR

Entire App on Heroku: https://auto-vaidya.herokuapp.com/ Frontend on Netlify: autovaidya.netlify.app

Owner
Smaranjit Ghose
Life Long Learner
Smaranjit Ghose
The official codes of "Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners".

SSL models are Strong UDA learners Introduction This is the official code of paper "Semi-supervised Models are Strong Unsupervised Domain Adaptation L

Yabin Zhang 26 Dec 26, 2022
Second-order Attention Network for Single Image Super-resolution (CVPR-2019)

Second-order Attention Network for Single Image Super-resolution (CVPR-2019) "Second-order Attention Network for Single Image Super-resolution" is pub

516 Dec 28, 2022
PyTorch code for Composing Partial Differential Equations with Physics-Aware Neural Networks

FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t

Cognitive Modeling 20 Dec 18, 2022
Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation.

Understanding Minimum Bayes Risk Decoding This repo provides code and documentation for the following paper: Müller and Sennrich (2021): Understanding

ZurichNLP 13 May 01, 2022
Implementation of Deformable Attention in Pytorch from the paper "Vision Transformer with Deformable Attention"

Deformable Attention Implementation of Deformable Attention from this paper in Pytorch, which appears to be an improvement to what was proposed in DET

Phil Wang 128 Dec 24, 2022
CenterPoint 3D Object Detection and Tracking using center points in the bird-eye view.

CenterPoint 3D Object Detection and Tracking using center points in the bird-eye view. Center-based 3D Object Detection and Tracking, Tianwei Yin, Xin

Tianwei Yin 134 Dec 23, 2022
Official PyTorch Implementation of Learning Architectures for Binary Networks

Learning Architectures for Binary Networks An Pytorch Implementation of the paper Learning Architectures for Binary Networks (BNAS) (ECCV 2020) If you

Computer Vision Lab. @ GIST 25 Jun 09, 2022
Irrigation controller for Home Assistant

Irrigation Unlimited This integration is for irrigation systems large and small. It can offer some complex arrangements without large and messy script

Robert Cook 176 Jan 02, 2023
API for RL algorithm design & testing of BCA (Building Control Agent) HVAC on EnergyPlus building energy simulator by wrapping their EMS Python API

RL - EmsPy (work In Progress...) The EmsPy Python package was made to facilitate Reinforcement Learning (RL) algorithm research for developing and tes

20 Jan 05, 2023
Hide screen when boss is approaching.

BossSensor Hide your screen when your boss is approaching. Demo The boss stands up. He is approaching. When he is approaching, the program fetches fac

Hiroki Nakayama 6.2k Jan 07, 2023
A collection of implementations of deep domain adaptation algorithms

Deep Transfer Learning on PyTorch This is a PyTorch library for deep transfer learning. We divide the code into two aspects: Single-source Unsupervise

Yongchun Zhu 647 Jan 03, 2023
Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation"

Medical-Transformer Pytorch Code for the paper "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" About this repo: This repo

Jeya Maria Jose 615 Dec 25, 2022
Post-Training Quantization for Vision transformers.

PTQ4ViT Post-Training Quantization Framework for Vision Transformers. We use the twin uniform quantization method to reduce the quantization error on

Zhihang Yuan 61 Dec 28, 2022
Pytorch code for our paper "Feedback Network for Image Super-Resolution" (CVPR2019)

Feedback Network for Image Super-Resolution [arXiv] [CVF] [Poster] Update: Our proposed Gated Multiple Feedback Network (GMFN) will appear in BMVC2019

Zhen Li 539 Jan 06, 2023
[ICCV 2021] Group-aware Contrastive Regression for Action Quality Assessment

CoRe Created by Xumin Yu*, Yongming Rao*, Wenliang Zhao, Jiwen Lu, Jie Zhou This is the PyTorch implementation for ICCV paper Group-aware Contrastive

Xumin Yu 31 Dec 24, 2022
Minimal fastai code needed for working with pytorch

fastai_minima A mimal version of fastai with the barebones needed to work with Pytorch #all_slow Install pip install fastai_minima How to use This lib

Zachary Mueller 14 Oct 21, 2022
[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV

Yongming Rao 90 Dec 31, 2022
Implement some metaheuristics and cost functions

Metaheuristics This repot implement some metaheuristics and cost functions. Metaheuristics JAYA Implement Jaya optimizer without constraints. Cost fun

Adri1G 1 Mar 23, 2022
Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies.

Crypto_Bot Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies. Steps to get started using the bot: Sign up

21 Oct 03, 2022
The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou, Quan Cui, Xiu-Shen Wei*, Zhao-Min Chen This repo

Megvii-Nanjing 616 Dec 21, 2022