semvec/pypi-packages huggingface dataset:
utilscool 1.0.0
A cool utility library
Requires Python: >=3.6

# notify

> This uses ntfy.sh
> Read their docs on ntfy.sh
> To receive notifcations you must download the ntfy.sh app and select a 'route' id

Parameters

route
> Route id

msg = ""
> msg content

title="<>"
> title

private = False
> Only sends the notifcation once when enabled, if the phone is not connected to the internet it will not receive it

priority = 3
> priority, only affects the app based on the settings chosen.
> Can be any integer from 1-5

action = None
> Used to create buttons linking to a url
```action = [("Google", "google.com"),("Example","example.com")] # [(label,url)] ```

delay=None
> Creates a delay

markdown_enabled = True
> Enables/Disables markdown

# pretty print
This replaces the print function when imported.
The new syntax is:
`print("Hello",end = " ",color=RED, move_cursor = START_OF_LINE)`

# plot
Just throw some values into it and it will plot them :)
`plot([1,2,4,8])`

# Database

First initialize a new database

`columns = [("name",str),("id",int),("score", float)]`

`data = Database("filename.db", columns)`

Now data can be used as a list of dictionaries :)

`data.append(("NAME1", 1, 1.1))`

`data[0]["id"] #-> 1`

# Retry

Decorator for use in debugging or web-requests
```
@retry(retries = 3, delay = 1, exponential_delay = True)
def myfunc():
    pass
```

# Timer

`start_timer()` - Stars/resets timer

`get_timer()` - Gets timer value as a `datetime` object
moveread-ocr 0.1.25
Moveread OCR model, in tensorflow
Requires Python: >=3.10

# Moveread OCR

## CLIs

### Data Exporting

```bash
ocr records boxes 'data/ocr-dataset/**/*' -vo path/to/tfrecords
ocr records samples 'data/ocr-dataset/**/*' -vo path/to/tfrecords
```

### Inference

```bash
ocr predict -v --weights model.weights.h5 --data path/to/tfrecords > top-preds.ndjson
```

### Finetuning

```bash
ocr finetune -vw model.weights.h5 --train path/to/tfrecords --val path/to/tfrecords \
  --epochs 20 --batch-size 32 --lr 0.001
```

### Evaluation

```bash
ocr evaluate -vw model.weights.h5 -d path/to/tfrecords
```

### Serving Export

```bash
ocr export -vw model.weights.h5 -o path/to/SavedModel
```
kspec-gfa-controller 0.6.0
The Controller software for KSPEC-GFA Camera
Requires Python: <4.0,>=3.10

# kspec_gfa_controller

![Versions](https://img.shields.io/badge/python-3.9+-blue)
![Ruff](https://github.com/mmingyeong/kspec_gfa_controller/actions/workflows/ruff.yml/badge.svg)
[![Documentation Status](https://readthedocs.org/projects/kspec-gfa/badge/?version=latest)](https://kspec-gfa.readthedocs.io/en/latest/?badge=latest)

# The KSPEC GFA Camera Controller
- KSPEC-GFA is a tool for guiding, focusing, and acquisition sequence control in KSPEC observation.
- The Controller communicate with Basler Guide cameras for guiding and focusing processes.
- The Controller use the [pypylon](https://github.com/basler/pypylon) library as the middleware for the communication.

# Getting Started

## Installation

`kspec-gfa` can be installed using by cloning this repository

```console
git clone https://github.com/mmingyeong/kspec_gfa.git
```

## Quick Start

```console
cd kspec_gfa_controller/controller/main.py
python main.py
```

## Software Architecture

Here is the Software Architecture diagram explaining the hierarchy of KSPEC-GFA.

![img](./docs/sphinx/source/_static/kspec-gfa_software_architecture.png)