semvec/pypi-packages huggingface dataset:
picture-comparator-muri 0.1.16
Finds similar images in chosen directory.
Requires Python: >=3.7

# picture-comparator

## Overview

Application looks for similar images in given directories. It allows to view results, make them easy to compare, move marked images to trash or rename them.

## Installation

```
pip install picture-comparator-muri
```

## Basic usage

After picking directories to search (either with GUI picker or `-d <list of directories>`) and waiting for a while, we should see list of results. Here, we have few tools helping us to compare them.
![](readme_images/screenshot_1.webp)
On the top of each image, we can see some of its properties. The "_best_" and "_worst_" ones should be marked in colors.  
We can zoom and move image using mouse. Position of all images will be in sync.
![](readme_images/screenshot_2.webp)
When comparing images with different sizes, the application will scale them.
![](readme_images/screenshot_3.webp)
Identical images are marked using little circles. This checks actual pixels, not file hash, so images with different compression levels or extensions can still be marked as identical.  
Symbolic links are also marked with an icon.
![](readme_images/screenshot_4.webp)
Clicking on "Mark for deleting" or holding down [Ctrl] key enables deleting mode. Selecting "delete" or clicking [del] moves files marked for deletion into trash.  
Selecting Edit -> Rename or clicking [F2] shows dialog for renaming and moving files.

## Known problems

The application is still in early development. Some known problems include.

- Very slow page change.
- Trouble when parsing many huge images.
- Comparison algorithm showing many false positives.
- Very limited configuration. 
- No option to start new search (need to restart application).
vad 1.0.2
VAD - Simple Voice Activity Detection

# VAD - simple voice activity detection in Python

This is a simple voice activity detection (VAD) algorithm in Python. It is based on simple energy-based thresholding and is intended to be used as a simple method for detecting speech in audio files when other methods cannot be used for both privacy, performance, or other reasons.

## Installation

You can install the package using pip:
```bash
pip install vad
```

## Usage

The package can be seamlessly integrated into your Python code. The following example shows how to use the package to detect speech in an audio file:

```python
from vad import EnergyVAD

# load audio file in "audio" variable

vad = EnergyVAD(
    sample_rate: int = 16000,
    frame_length: int = 25, # in milliseconds
    frame_shift: int = 20, # in milliseconds
    energy_threshold: float = 0.05, # you may need to adjust this value
    pre_emphasis: float = 0.95,
) # default values are used here

voice_activity = vad(audio) # returns a boolean array indicating whether a frame is speech or not

# you can also use the following method to get the audio file with only speech
# speech_signal is a numpy array of the same shape as audio
speech_signal = vad.apply_vad(audio)
```

## Audio samples

- `example.wav` is a sample audio file that can be used to test the package.
- `example_vad.wav` is the audio file with only speech after applying the VAD algorithm.
- `example_vad_2.wav` is the audio file with only speech direcly extracted from the original audio file using the `apply_vad` method.
- `vad_output.png` is a plot of the voice activity detected by the VAD algorithm.
- `test_vad.py` is the script that was used to generate the above audio files and plot.

## Known issues

- There is no additional VAD algorithm implemented in this package at the moment. It may be added in the future.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.