Unsupervised clustering of high content screen samples

Overview

Microscopium

Unsupervised clustering and dataset exploration for high content screens.

Build Status Coverage Status Gitter

See microscopium in action

microscopium_bbbc021

Public dataset BBBC021 from the Broad Bioimage Benchmark Collection with t-SNE image embedding.

For developers

We encourage pull requests - please get in touch if you think you might like to contribute.

License

This project uses the 3-clause BSD license. See LICENSE.txt.

Development installation

First, clone this repository, and change into its directory:

git clone https://github.com/microscopium/microscopium.git
cd microscopium

Then, install the dependencies via one of the below methods

conda, new environment (recommended)

conda env create -f environment.yml
conda activate mic

conda, existing environment

# conda activate <env-name>
conda install -f environment.yml

pip

pip install -r requirements.txt

Finally, install microscopium, optionally as an editable package:

pip install [-e] .

Serving the web app

Supported browsers are Chrome and Firefox. However we have observed that performance is much better on Chrome. (Unfortunately, we do not currently support Safari or Internet Explorer.)

Your data needs to have the following format:

  • a collection of image files (can be in a directory, or in a nested directory structure)
  • a .csv file containing, at a minimum, the x/y coordinates of each image, and the path to the image in the directory. The path should be relative to the location of the .csv file.
  • a .yaml file containing settings. At a minimum, it should contain an embeddings field with maps from <embedding name> to column names for x and y, as well as image-column containing the name of the column containing the path to each image. If you don't want to specify the settings file path, place settings.yaml next to the .csv file. Microscopium will look here by default.

For example data, see:

  • tests/testdata/images/*.png
  • tests/testdata/images/data.csv
  • tests/testdata/images/settings.yaml

To run the web app locally, try:

python -m microscopium.serve tests/testdata/images/data.csv -c tests/testdata/images/settings.yaml

You should then be able to see the app in your web browser at: http://localhost:5000

You can specify a port number with -P.

python -m microscopium.serve tests/testdata/images/data.csv -P 5001

This specifies the port number as 5001, and the app will run locally at: http://localhost:5001/

For more information, run python -m microscopium.serve --help

GluonMM is a library of transformer models for computer vision and multi-modality research

GluonMM is a library of transformer models for computer vision and multi-modality research. It contains reference implementations of widely adopted baseline models and also research work from Amazon

42 Dec 02, 2022
Official implementation of NeurIPS 2021 paper "Contextual Similarity Aggregation with Self-attention for Visual Re-ranking"

CSA: Contextual Similarity Aggregation with Self-attention for Visual Re-ranking PyTorch training code for CSA (Contextual Similarity Aggregation). We

Hui Wu 19 Oct 21, 2022
Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab

PySDM PySDM is a package for simulating the dynamics of population of particles. It is intended to serve as a building block for simulation systems mo

Atmospheric Cloud Simulation Group @ Jagiellonian University 32 Oct 18, 2022
Elevation Mapping on GPU.

Elevation Mapping cupy Overview This is a ros package of elevation mapping on GPU. Code are written in python and uses cupy for GPU calculation. * pla

Robotic Systems Lab - Legged Robotics at ETH Zürich 183 Dec 19, 2022
A modular active learning framework for Python

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

modAL 1.9k Dec 31, 2022
Official PyTorch code for the paper: "Point-Based Modeling of Human Clothing" (ICCV 2021)

Point-Based Modeling of Human Clothing Paper | Project page | Video This is an official PyTorch code repository of the paper "Point-Based Modeling of

Visual Understanding Lab @ Samsung AI Center Moscow 64 Nov 22, 2022
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open

19.4k Jan 04, 2023
Chinese Mandarin tts text-to-speech 中文 (普通话) 语音 合成 , by fastspeech 2 , implemented in pytorch, using waveglow as vocoder,

Chinese mandarin text to speech based on Fastspeech2 and Unet This is a modification and adpation of fastspeech2 to mandrin(普通话). Many modifications t

291 Jan 02, 2023
Awesome Long-Tailed Learning

Awesome Long-Tailed Learning This repo pays specially attention to the long-tailed distribution, where labels follow a long-tailed or power-law distri

Stomach_ache 284 Jan 06, 2023
A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

TorchRL Disclaimer This library is not officially released yet and is subject to change. The features are available before an official release so that

Meta Research 860 Jan 07, 2023
Constrained Logistic Regression - How to apply specific constraints to logistic regression's coefficients

Constrained Logistic Regression Sample implementation of constructing a logistic regression with given ranges on each of the feature's coefficients (v

1 Dec 29, 2021
OBBDetection is a oriented object detection library, which is based on MMdetection.

OBBDetection news: We are now updating OBBDetection to new vision based on MMdetection v2.10, which has more advanced models and more efficient featur

jbwang1997 401 Jan 02, 2023
Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions

Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictions Usage Clone the code to local. https://github.com/tanlab/MI

Computational Biology and Machine Learning lab @ TOBB ETU 3 Oct 18, 2022
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

Semi-supervised-learning-for-medical-image-segmentation. Recently, semi-supervised image segmentation has become a hot topic in medical image computin

Healthcare Intelligence Laboratory 1.3k Jan 03, 2023
Multilingual Image Captioning

Multilingual Image Captioning Authors: Bhavitvya Malik, Gunjan Chhablani Demo Link: https://huggingface.co/spaces/flax-community/multilingual-image-ca

Gunjan Chhablani 32 Nov 25, 2022
Reinforcement Learning for Automated Trading

Reinforcement Learning for Automated Trading This thesis has been realized for the obtention of the Master's in Mathematical Engineering at the Polite

Pierpaolo Necchi 80 Jun 19, 2022
A PyTorch implementation of "CoAtNet: Marrying Convolution and Attention for All Data Sizes".

CoAtNet Overview This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021

Justin Wu 268 Jan 07, 2023
Multispectral Object Detection with Yolov5

Multispectral-Object-Detection Intro Official Code for Cross-Modality Fusion Transformer for Multispectral Object Detection. Multispectral Object Dete

Richard Fang 121 Jan 01, 2023
Robust Self-augmentation for NER with Meta-reweighting

Robust Self-augmentation for NER with Meta-reweighting

Lam chi 17 Nov 22, 2022
Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.

Accommodating supervised learning algorithms for the historical prices of the world's favorite cryptocurrency and boosting it through LightGBM.

1 Nov 27, 2021