semvec/pypi-packages huggingface dataset:
easy-augment 1.1.0
End to end software to capture new objects using RGBD camera  and augment them to get a annotated dataset to train deep nets.
License: MIT


# Easy Augmentor


> End to end software to capture new objects using RGBD camera and augment them to get a annotated dataset to train deep nets

1) Pipeline to artificial generate annotated data for training deep learning models.
2) Pipeline includes starting from capturing images using provided camera (Realsense),
generate semantic labels of the captured image and then generate the artificial images.
3) GUI required for the end user from capturing to labelling and generating new data.

![](header.png)
## Requirements
1) Ubuntu 16.04 (Testing for Ubuntu 18.04)
2) Intel Realsense Camera
3) Processer intel i5 or higher
4) libpcl-dev==1.7
5) python 3.5

## Limitations
1) Number of classes captured should be more than or equal to 2.

## Installation

Linux:

```sh
pip3 install easy-augmentor
```



## Release History


* 1.0.0
    * First release for crowd testing
* 1.1.0
    * Now user can save RGB, pointcloud, depth, boundingbox, semantic label
    * Continous mode added

## Contributors
* Santosh Muthireddy              – https://github.com/santoshreddy254
* Naresh Kumar Gurulingan         - https://github.com/NareshGuru77
* Deepan Chakravarthi Padmanabhan - https://github.com/DeepanChakravarthiPadmanabhan
* M.Sc Deebul Nair                - https://github.com/deebuls


Distributed under the MLP license. See ``LICENSE`` for more information.
nanome-chemical-properties 0.3.5
A Nanome plugin to display chemical properties for a complex using rdkit
License: MIT
Keywords: virtual-reality,chemistry,python,api,plugin

# Nanome - Chemical Properties

A Nanome plugin to display chemical properties for a complex using rdkit

### Installation

```sh
$ pip install nanome-chemical-properties
```

### Dependencies

This plugin requires `rdkit` to be installed and in the `PATH` variable.

Installation instructions for `rdkit` can be found [here](http://www.rdkit.org/docs/Install.html)

### Usage

To start the plugin:

```sh
$ nanome-chemical-properties -a <plugin_server_address>
```

### Docker Usage

To run in a Docker container:

```sh
$ cd docker
$ ./build.sh
$ ./deploy.sh -a <plugin_server_address>
```

#### Basic properties

In Nanome:

- Activate Plugin
- Select Properties
- Select Complex
- View Results

#### Snapshots

`nanome-chemical-properties` has a "snapshots" feature where you can take a snapshot of a complex to compare properties against other snapshots. Snapshots only persist while the plugin is active, so deactivating the plugin will lose the current snapshots.

To create a snapshot, select a complex and press the "snapshot" button.

To view a table comparison of your snapshots, press the "view snapshots" button.

In the snapshots view:

- Pressing a column header will switch through the sorting options for that column. Pressing it once will sort ascending, a second time will sort descending, and a third time will remove sorting on that column.
- Pressing on a snapshot row will bring up a window containing a 2D rendering of the snapshot, as well as the snapshot timestamp and options to rename, load, or delete the snapshot.
- Pressing "export csv" will save the snapshot names, SMILES string, and properties to ~\Documents\nanome\snaphots on the computer running Nanome.

### License

MIT
monilog 0.1.4
HTTP log monitoring
License: MIT
Keywords: HTTP log monitoring

# Monilog

[![Build Status](https://travis-ci.org/tayciryahmed/monilog.svg?branch=master)](https://travis-ci.org/tayciryahmed/monilog)
[![codecov](https://codecov.io/gh/tayciryahmed/monilog/branch/master/graph/badge.svg)](https://codecov.io/gh/tayciryahmed/monilog)
[![PyPI Version](https://img.shields.io/pypi/v/monilog.svg)](https://pypi.org/project/monilog/)


This project allows watching and logging all HTTP traffic of a system, generating log in w3c log format, showing statistics about total requests, maximum hits, requests in a timespan and alerting when traffic is above a customizable threshold.

## Requirements

* Python and preferably Linux.

## Usage
* You can execute `simulate.sh` to run a simulation of how this project works. The simulation setup is customisable, feel free to play with it.

* Make sure to install the package by runing : 

```
python setup.py install 
```

or 

```
pip install monilog
```



* To run the monitoring in your own log file, run: 

```
monitoring --file /path/to/your/file --threshold 10
```

* To customize the log generation, run: 

```
log_generator --rates 9 11 8 --durations 150 150 150
```

With `rates` being the number of requests per second for each step of the simulation and `durations` being the durations of the corresponding simulation steps.

* To execute the tests , run :

```
nosetests --with-coverage --cover-package=monilog
```

**Attention:** The monitoring is stopped when no new logs are written to the log
file during `MAX_IDLE_TIME` set by default to 2 minutes. This is added to manage stopping
the monitoring automatically, particularly when doing limited time simulations. 


## Future Improvements
This is a first working solution for http log monitoring. Many improvements can be added : 
* Managing threaded access to the log file using cross-platform file locking. The current implementation is tested on Linux and may
cause errors in Windows. 
* Enhancing the display of the log analysis and statistics. For now, the monitoring results are written 
to standard output and to a log file with the naming convention `simulation-<timestamp>.log`. A better setup would be to customize the 
GUI using [npyscreen](https://pypi.org/project/npyscreen/) for instance. 
* It is also possible to build a live dashboard consuming `simulation-<timestamp>.log` data and mapping it to graphs. 
* Pushing alerting notifications by email or SMS to admins / owners of the monitored system. 
* Adding more relevant statistics to the analysis of the website and handle timezone changes.
* Writing extensive unit and integration tests.
* For a higher scale of data requiring high availability in a production setup, a more robust solution would be indexing the logs in ElasticSearch and building Kibana dashboards, with a stream-processing platform such as Kafka.
pychemin 0.0.1.dev2
A minimal language to describe interactive, terminal-based text adventure games
License: MIT
Requires Python: >=3.6,<4.0

# PyChemin

I'm in the process of decoupling PyChemin from its inception's repository, [Hyperis](github.com/ewen-lbh/hyperis) -- a terminal-based adventure game.

A proper README + GitHub page will soon be available.

In the meantime, if you can read french, you can [learn PyChemin's syntax](ewen-lbh.github.io/hyperis)