semvec/pypi-packages huggingface dataset:
VideoScripy 0.0.1
Collection of video processes such as Optimize, Upscale and Interpolation.
Requires Python: >=3.10
Keywords: ffmpeg, upscale, interpolate, video process


# VideoScripy

VideoScripy is a collection of video processes including video Optimization, Upscale and frame Interpolation.

It uses Python to generate **FFmpeg**, **Real-ESRGAN** and **IFRNet** command line script to performes serial processing on scanned mp4 and mkv videos.

**⚠ Only compatible with Windows users who have Nvidia cards.**



## Requirements

- Windows OS

- NVIDIA card

Following tools in the environment variable **PATH** :

- [FFmpeg](https://www.gyan.dev/ffmpeg/builds/), full build for hardware acceleration.

- [Real-ESRGAN-ncnn-vulkan](https://github.com/xinntao/Real-ESRGAN-ncnn-vulkan/releases) for video upscaling.

- [Ifrnet-ncnn-vulkan](https://github.com/nihui/ifrnet-ncnn-vulkan/releases) for video frame interpolation.  



## Usage

```python
from videoscripy import VideoScripy

vs = VideoScripy(__file__)

# get current folder video(s)
vs.getVideo(folderDepthLimit=0)
vs.getVideoInfo()

# run process(es)
vs.optimize()
# vs.resize()
# vs.upscale()
# vs.interpolate()
# vs.merge()
```

Or directly call vscli.exe




## Processes Description

- optimize

    Reduce the video biteRate in order to gain storage space.  
    The processed videos will have a bitRate = width * height * quality, which quality=3 is generally the lowest value before appearance of artifacts (bad images, blurry...). In other words, humain wont notice the visual difference between video of quality 3 and 6.

- resize

    Reduce the video width and height.

- upscale

    Recover old video from 360p to 4K, enhance video quality.  
    Begin with a transformation of video to image frames, then upscale each frames, finally reassemble to video.   
    It has the ability to start from last upscal progress if the "_upscaled_frame" wasn't deleted.

- interpolate

    Increase video frame rate (FPS), smooth video motions.  
    Begin with a transformation of video to image frames, then interpolate between frames, finally reassemble to video.

- merge

    Merge all video, including each of its audio and subtitle by option, into mkv. Then use media player as PotPlayer to switch between video/audio/subtitle.



## Credits

This project relies on the following software and projects.
- [alive-progress](https://github.com/rsalmei/alive-progress)
- [Real-ESRGAN](https://github.com/xinntao/Real-ESRGAN)
- [IFRNet](https://github.com/ltkong218/IFRNet)
- [FFmpeg](https://www.ffmpeg.org/)



## TODO list

- ✅ Stop upscale and interpolate process
- ✅ Get video walk optimize
- [ ] Check tools
- [ ] Sort by name
- [ ] replace "&" by "x" in video name
- [ ] Add FFmpeg visual quality metrics (PSNR, SSIM, VMAF)
- [ ] Better hevc_nvenc parameters
- [ ] Better upscale recovery
mtqdm 0.1.4a1
Put tqdm on your menu bar.
Requires Python: >=3.12
Keywords: progress, progressbar, menubar, tqdm, macos

# mtqdm v0.1.4a1

> ⚠️ **Warning**: This project is VERY MUCH in alpha. While it works (a little bit), it was written in a single sitting exclusively using Cursor; which is amazing but also means I haven't authored a single line of code, or even read through tqdm, or rumps' docs. Expect major rough edges, but improvements are actively being made. Especially since this is a tool I'll be using myself.

Put tqdm on your menu bar.

## Usage

```bash
pip install mtqdm
```

My intentions for mtqdm is for it to be a *drop-in replacement* for **tqdm**.
So simply replace **tqdm** with **mtqdm** in your code.

```python
from mtqdm import mtqdm
for _ in mtqdm(range(100)):
    # ...
```

![mtqdm-0.1.4a1 in action](https://github.com/0oj/mtqdm/blob/main/examples/basic_usage.png?raw=true)

The progress bar from **tqdm** will still be displayed in the terminal. Additionally, a progress bar like the one above will appear in the menu bar. Clicking it will reveal metrics.

`100%|████████████████████| 100/100 [00:15<00:00,  6.50it/s]`
bts7960-micropython 0.0.1
Project to manage H-Brigde model BTS7960 with micropython
Keywords: micropython, electronics, esp32, hbridge, h-bridge, bts7960


# bts7960-micropython



`bts7960-micropython` is a Python library to control a motor driver using the **BTS7960 H-Bridge** IC. This library allows you to control the motor speed and direction through PWM (Pulse Width Modulation) signals using a microcontroller like the ESP32 or ESP8266.



## Features



- Control motor direction (forward/reverse)

- Control motor speed (from -100 to 100)

- Easy-to-use API for integrating into projects



## Installation



### Install via pip (once available on PyPI)



```bash

pip install bts7960-micropython
gumsh-py 1.1.1
gumsh_py is a Python interface of charm.sh's shell tool called gum
Requires Python: >=3.8

# gumsh_py
gumsh_py is a Python interface of charm.sh's shell tool called [gum](https://github.com/charmbracelet/gum). Gum is used to create aesthetically pleasing shell scripts. 

# Installation
Install gum for your environment using the [instructions](https://github.com/charmbracelet/gum).
Then install my python package like so:
```sh
$ pip install gumsh-py
```

# Usage
```python
from gumsh_py import gumsh_py as gp

gumpy.choose(prompt="favorite languages?", options=["python", "javascript", "java", "c++", "c#"])
gumpy.spin(command="sleep 5", show_output=False, spinner="dot", text="Sleeping...")
print(gumpy.confirm(prompt="Are you positive?"))
gumpy.get_input(prompt="Enter your name:", placeholder="John Doe")
gumpy.log(text="Hello, World!", level="info", time="ansic")
```

# Note
Not all command flag options in the gum library are given for each command. And not all commands are included. If this package picks up steam, I will consider adding support.
E.g. `gum choose` for example allows for a limit which I have included functionality for, but there are other [options](https://github.com/charmbracelet/gum/blob/main/choose/options.go) such as `CursorPrefix` that are not included for simplicity's sake. 

To view flags that the Python package uses, go to the [gum](https://github.com/charmbracelet/gum) repository, choose the command you are using `choose` for example, and open the `options.go` file to view flag options. 

# Pypi
[Pypi](https://pypi.org/project/gumsh-py/) details.
Portables 0.1
Descripción breve de tu paquete

# APPLEE: Automated Preprocessing Pipeline for Low-Electrode Encephalography

```
Authors: Luisa Maria Zapata S., Juliana Moreno Rada, Eduardo Montoya G., Santiago Gonzalez C., David F. AguillÃ³n N., Carlos A. TobÃ³n Q. ,John F. Ochoa G.
```


![image](https://github.com/user-attachments/assets/273d7022-637c-4f7a-a164-4bdd9f4812b8)