semvec/pypi-packages huggingface dataset:
covfee 0.0.36
Continuous video feedback tool
Requires Python: >=3.6

# covfee: continuos video feedback tool.

Covfee was created to provide an easily extensible tool for video perception and annotation experiments, especially those requiring continuous feedback from the user.

Full documentation: [covfee docs](https://josedvq.github.io/covfee/)

## Quick start

This document contains instructions for installing covfee locally. We recommend that you work with covfee locally first even if you plan to put it online.

### Setup

1. Install version 12.x of [node.js](https://nodejs.org/en/download/). Make sure that the `npm` command is available in your terminal.

2. Clone this repository and install covfee using pip:

```
git clone git@github.com:josedvq/covfee.git
cd covfee
python3 -m pip install -e .
```

3. Install Javascript dependencies:
```
covfee-installjs
```

### Getting started

Please see the [covfee docs](https://master--5faeef49f6655f00210dbf35.chromatic.com) for an interactive getting started guide.

## Changing covfee
If you wish to change the source code of the backend or make changes to the frontend that are not supported by a custom task, see the [Development guide](docs/development.md).
SiQ3D 0.1.0
Deep Learning-based 3D single-cell imaging analysis pipeline for quantifying cell-cell interaction dynamics
Requires Python: >=3.8

This Python-based software tool, SiQ-3D (Single-cell image Quantifier for 3D), optimizes Deep Learning (DL)-based 3D image segmentation, single-cell phenotype classification and tracking to automatically quantify and convert 3D live-cell imaging movies into multi-dimensional dynamic data for different interacting cell types in a 3D tissue/organ microenvironment. The SiQ-3D quantified results are output in an excel file of cell position and phenotype at each time point together with labelled images of the segmented single cells for each cell type in the imaging dataset. SiQ-3D can be easily customized to analyze 3D microscopy data from both in vitro and in vivo imaging of diverse tissue/organ models that comprise multiple interacting cell types.
python-switchbot-ble 0.1.0
A capable Python library for controlling Switchbot devices over Bluetooth Low Energy (Without a Hub)
Requires Python: >=3.7

# Python SwitchBot BLE

A reverse engineered Bluetooth Low Energy Python API for the SwitchBot Bot. 

## Installation

```
$ pip install python-switchbot-ble
```

## Usage

`examples` folder gives basic implementations


Originally made for Cyber Physical Systems Security.