semvec/pypi-packages huggingface dataset:
mecompyapi 0.0.3
A Python API for the MeCom protocol by Meerstetter.
Requires Python: >=3.9

# MeComPyAPI
A Python API for the MeCom protocol by Meerstetter.

## Overview
The source code and example scripts have been tested using Python 3 running in Windows 10.

1. Project Homepage: https://github.com/houlihaj/MeComPyAPI
1. Download Page: https://pypi.org/project/mecompyapi/

## Requirements
1. `pyserial` in a version `>= 3.5` https://pypi.org/project/pyserial/
1. `pythoncrc` in a version `>= 1.21` https://pypi.org/project/pythoncrc/
1. `ftd2xx` in a version `>= 1.3.6` https://pypi.org/project/ftd2xx/

## Installation
1. `pip install mecompyapi`

## Usage
There are a number of examples in the `examples` directory that can help you get up and running.
bf-monitor 0.0.5
filesystem monitor for b!
Requires Python: >=3.11

# Project Template

`./dev.sh` automates common development tasks. Feel free to add new ones! Change `NAME` and `USER` at the top of `./dev.sh` before use. GPLv3 License included (`./LICENSE`), keep or change for your project.

External dependencies:
- [Anaconda](https://docs.anaconda.com/free/anaconda/install/index.html) / [Mamba (multithreaded Anaconda)](https://mamba.readthedocs.io/en/latest/mamba-installation.html#mamba-install)
- [Docker](https://docs.docker.com/engine/install/)
- [Singluarity (requires docker)](https://apptainer.org/admin-docs/master/installation.html)

A quick sample:

- `./dev.sh -bc` to build <b>conda package</b>
- `./dev.sh -bd` to build <b>docker container</b>
- `./dev.sh -bd` to run source
- other scripts include uploading to anaconda, running `./src` locally, and testing containers

### Setting up the environment

`./dev.sh -idev`

Creates a new conda environement using the `base.yml` and `dev.yml` files at `./envs`

### Running locally

`./dev.sh -r`

Runs the python package at `./src/*` directly

### Conda

Requires the development environment and anaconda.org account if uploading. Add dependencies under `./envs/base.yml`.

1. bump the version at `./src/<PACKAGE>/version.txt`
1. build pip package `./dev.sh -bp`
1. build conda package using the pip package `./dev.sh -bc`
1. upload to your channel `./dev.sh -uc`

### Docker / Singularity

1. configure `./Dockerfile`
1. build container `./dev.sh -bd`
1. upload to quay.io `./dev.sh -ud`
1. build singularity from docker `./dev.sh -bs` (not dependent on upload)
openmc-cylindrical-mesh-plotter 0.3.3
A Python package for creating plots of OpenMC cylindrical mesh tallies
Requires Python: >=3.8
Keywords: cylindrical, mesh, openmc, tally, plot, slice

[![CI with install](https://github.com/fusion-energy/openmc_cylindrical_mesh_plotter/actions/workflows/ci_with_install.yml/badge.svg)](https://github.com/fusion-energy/openmc_cylindrical_mesh_plotter/actions/workflows/ci_with_install.yml)

# openmc_cylindrical_mesh_plotter

Plots R-Z or Phi-R slices of OpenMC cylindrical mesh tallies


![openmc cylinder PhiR mesh tally plot](https://user-images.githubusercontent.com/8583900/227660135-8ac2eb69-829c-4788-ae02-f9e4b1465aa6.png)
![openmc cylinder RZ mesh tally plot](https://user-images.githubusercontent.com/8583900/227660142-99bcb264-57f8-47d6-b9ff-d211645fe185.png)
![openmc cylinder RZ mesh tally plot with outline](https://github.com/fusion-energy/openmc_cylindrical_mesh_plotter/assets/8583900/65d222f0-5070-4705-ab99-805e4df49a81)


## Installation

openmc_cylindrical_mesh_plotter is available on PyPi

```bash
pip install openmc_cylindrical_mesh_plotter
```

Install with the optional Graphical User Interface (GUI)

```bash
pip install openmc_cylindrical_mesh_plotter[gui]
```

## API Usage

See the [examples](https://github.com/fusion-energy/openmc_cylindrical_mesh_plotter/tree/main/examples) folder for example scripts

## Graphical User Interface Usage

Once installed you should be able to type the following command from the terminal and the GUI will launch in a browser window.

```bash
openmc_cylindrical_mesh_plotter
```

![openmc cylinder mesh plot GUI](https://user-images.githubusercontent.com/8583900/228016577-d5d9f541-1b4d-4d9b-a207-f3f1d08e27a8.gif)
gradio-sbmp-promptable-image 0.0.3
A webcam-compatible Gradio input image component enabling prompting with the most recently drawn bounding box and multiple points.
Requires Python: >=3.8
Keywords: gradio-custom-component, gradio-template-Image


# `gradio_sbmp_promptable_image`

A webcam-compatible Gradio input image component enabling prompting with the most recently drawn bounding box and multiple points.

## Installation

```bash
pip install gradio_sbmp_promptable_image
```

## Usage

```python

import gradio as gr
from gradio_sbmp_promptable_image import SBMPPromptableImage
import cv2

BLUE = (135, 206, 235)
PINK = (239, 149, 186)

image_examples = [{"image": "images/cat.png", "points": []}]

def get_point_inputs(prompts):
    point_inputs = []
    for prompt in prompts:
        if prompt[5] == 4.0:
            point_inputs.append((prompt[0], prompt[1], prompt[2]))

    return point_inputs

def get_box_inputs(prompts):
    box_inputs = []
    for prompt in prompts:
        if prompt[2] == 2.0 and prompt[5] == 3.0:
            box_inputs.append((prompt[0], prompt[1], prompt[3], prompt[4]))

    return box_inputs

def process_input(input_dict):
    img, points = input_dict['image'], input_dict['points']

    point_inputs = get_point_inputs(points)
    box_inputs = get_box_inputs(points)

    for point in point_inputs:
        x, y = int(point[0]), int(point[1])
        cv2.circle(img, (x, y), 2, (0, 0, 0), thickness=10)
        if point[2] == 1:
            cv2.circle(img, (x, y), 2, BLUE, thickness=8)
        else:
            cv2.circle(img, (x, y), 2, PINK, thickness=8)

    for box in box_inputs:
        x1, y1, x2, y2 = int(box[0]), int(box[1]), int(box[2]), int(box[3])
        cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2)

    return img

demo = gr.Interface(
    process_input,
    SBMPPromptableImage(),
    gr.Image(),
    examples=image_examples,
)

if __name__ == "__main__":
    demo.launch()

```

## Acknowledgements

Special thanks to the creators of [gradio-image-prompter](https://github.com/PhyscalX/gradio-image-prompter/tree/main?tab=readme-ov-file) - this custom component is heavily adapted from their work.