semvec/pypi-packages huggingface dataset:
solveit-tools 0.1.0
A comprehensive toolkit for data processing and problem-solving
Requires Python: >=3.7

# SolveIt Tools

[![PyPI version](https://badge.fury.io/py/solveit-tools.svg)](https://badge.fury.io/py/solveit-tools)
[![Python 3.7+](https://img.shields.io/badge/python-3.7+-blue.svg)](https://www.python.org/downloads/release/python-370/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

A comprehensive Python toolkit for data processing and problem-solving.

## Features

- **Data Cleaning**: Advanced tools for handling missing values, outliers, and duplicates
- **Unit Conversion**: Comprehensive unit conversion system
- **Pathfinding**: Implementation of various pathfinding algorithms
- **Financial Calculations**: Tools for financial computations
- **Time Management**: Scheduling and timeline optimization
- **Visualization**: Easy-to-use plotting utilities

## Installation
cvvideoplayer 1.2.9
moduler multi purpose video player for debugging algorithms in python
Requires Python: >=3.8
Keywords: opencv, video, player, video player, cvvideoplayer, computer vision, image processing, customizable


<div align="center"><img src=https://github.com/user-attachments/assets/2842b031-0075-454e-b4e4-cfe0e95cb1af width="250"></div>
<div align="center"><img src=https://github.com/user-attachments/assets/e05b0d77-2e67-4b4b-b28f-8a0797dfb169 width="900"></div>


## Introduction
CV video player is a Python-based customizable video player that helps computer vision practitioners
develop, analyze, and debug their video-related algorithms and models.

The video player is made with simplicity in mind to allow users to easily add or remove functionality.
It is only based OpenCV with no additional GUI frameworks, and
It's interactivity is based on keyboard presses (no buttons).

The player is designed as a callback system. When initialized the player receives a 
list of callbacks, each with a `edit_frame` method.
On runtime the callbacks will run in order as specified in the input list. Each callback can also optionally add 
keyboard shortcuts to change visualization settings in real time.

## Installation
`pip install cvvideoplayer`

## Quick Start

```python
from cvvideoplayer import create_video_player
from cvvideoplayer.frame_editors import FrameInfoOverlay, KeyMapOverlay, FitFrameToScreen

VIDEO_OR_FRAME_FOLDER_PATH = "<add local path here>"


def run_player():
    video_player = create_video_player(
        video_source=VIDEO_OR_FRAME_FOLDER_PATH,
        frame_edit_callbacks=[
            FitFrameToScreen(),
            FrameInfoOverlay(),
            KeyMapOverlay(),
        ],
        record=True,
    )

    video_player.run()


if __name__ == "__main__":
    run_player()
``` 

In this example, we initiate a very basic video player that will play "example_video.mp4" with added basic
frame edit callbacks:
- `FitFrameToScreen`: Resizes the frame to fit the screen size
- `FrameInfoOverlay`: Prints the current frame number and original frame resolution in the top left corner
- `KeyMapOverlay`: prints all optional shortcuts registered by all callbacks

Check out the `./demos` folder which shows the use of other cool frame edit callback
such as `OpticalFlow` and `DetectionCsvPlotter`
## See it in action
<details>
<summary>Running frame by frame</summary>
    
![frame_by_frame](https://github.com/danieltomer1/CVVideoPlayer/assets/163285251/7db8cb8c-0075-416c-9901-aa2f4bb49080)
</details>

<details>
<summary>Play/Pause and control play speed and direction</summary>
    
![playpause](https://github.com/danieltomer1/CVVideoPlayer/assets/163285251/fcf38b37-ec9c-4250-8c2f-6f123154c1e4)
</details>

<details>
<summary>Draw bounding boxes and adjust labels</summary>
    
![bboxes](https://github.com/danieltomer1/CVVideoPlayer/assets/163285251/0a6e07de-a015-48b4-b510-2c203e0d69f4)
</details>
copernicus-checker 1.0.2
A Python package for checking duplicate dataset requests in Copernicus projects.
Requires Python: >=3.6

# Checker

`checker` is a Python package that helps prevent redundant downloads from Copernicus Marine datasets by leveraging MongoDB to check for duplicate requests.

## Installation

You can install the package using `pip`:

```bash
pip install checker==1.0.1

```
To use the duplication system for python api, import the following

```bash
in case of copernicusmarine
import copernicus_python_api

in case of cds
import cds_python_api
```

To use the duplication system for CLI, run the following commands

```bash
in case of copernicusmarine

python /path/to/copernicus_cli.py copernicusmarine subset --dataset-id ...

in case of ceda

python /path/to/ceda_cli.py wget ...

```
maths-toolkit 2.0.0
A toolkit for intermediate-level Maths A and Maths B calculations.
Requires Python: >=3.6

# Maths Toolkit
# Author : N V R K SAI KAMESH SHARMA
---
Maths Toolkit is a Python library designed to simplify intermediate-level mathematics calculations for both Maths A (Algebra) and Maths B (Trigonometry, Calculus, and more). It provides easy-to-use functions for common operations, making it ideal for students, educators, and developers.

## Features

### Algebra (Maths A)
- Solve quadratic equations.
- Matrix operations (addition, multiplication, transpose).

### Trigonometry (Maths B)
- Sine, cosine, and other trigonometric functions (in degrees).

### Calculus (Maths B)
- Differentiate polynomials.
- Integrate polynomials.

### Statistics
- Calculate mean, variance, and standard deviation.

## Installation

Install Maths Toolkit using pip:

```bash
pip install maths-toolkit
```

## Usage

Here's how to use Maths Toolkit:

### Example: Solving Quadratic Equations
```python
from maths_toolkit import MathsToolkit

# Solve x^2 - 5x + 6 = 0
roots = MathsToolkit.solve_quadratic(1, -5, 6)
print("Roots:", roots)
```

### Example: Trigonometry
```python
# Calculate sin(30 degrees)
sine = MathsToolkit.sin_deg(30)
print("Sin 30°:", sine)
```

### Example: Calculus
```python
# Differentiate 3x^2 + 2x + 1
derivative = MathsToolkit.differentiate([3, 2, 1])
print("Derivative:", derivative)

# Integrate 3x^2 + 2x + 1
integral = MathsToolkit.integrate([3, 2, 1])
print("Integral:", integral)
```

### Example: Statistics
```python
# Data set
data = [1, 2, 3, 4, 5]

# Calculate mean, variance, and standard deviation
mean = MathsToolkit.mean(data)
variance = MathsToolkit.variance(data)
std_dev = MathsToolkit.standard_deviation(data)

print("Mean:", mean)
print("Variance:", variance)
print("Standard Deviation:", std_dev)
```

### Example: Matrix Operations
```python
# Matrices
a = [[1, 2], [3, 4]]
b = [[5, 6], [7, 8]]

# Matrix addition
addition = MathsToolkit.matrix_add(a, b)
print("Matrix Addition:", addition)

# Matrix multiplication
multiplication = MathsToolkit.matrix_multiply(a, b)
print("Matrix Multiplication:", multiplication)

# Matrix transpose
transpose = MathsToolkit.matrix_transpose(a)
print("Matrix Transpose:", transpose)
```

## Future Plans
- Expand support for advanced calculus.
- Include graphical visualizations.

## Contributing

Contributions are welcome! If you'd like to contribute, please fork the repository and submit a pull request with your changes.

## License

This project is licensed under the MIT License. See the `LICENSE` file for details.

## Author

N V R K Sai Kamesh Sharma

For questions or feedback, feel free to reach out at [your-email@example.com].
wangph 0.0.2
wangph lib for 3d vision

# wangph
The python lib for wangph's project

## Install
```
pip install wangph
```

## Documentation
Under construction

## Acknowledgement
The source code refers to the following projects:
- [kiui](https://kit.kiui.moe/)
- [gaussian-splatting](https://github.com/graphdeco-inria/gaussian-splatting)