semvec/pypi-packages huggingface dataset:
unicodecheck 1.2.6
A simple tool to check if Unicode text files are Unicode-normalized
Requires Python: >=3.11
Keywords: Unicode, character encoding

# Unicodecheck

A simple tool to check if Unicode text files are Unicode-normalized

## Install

```sh
pip install unicodecheck
```

## Usage

### Quickstart

```sh
unicodecheck -iv SPAM.txt
```

To check files in a directory recursively:

```sh
unicodecheck -ivr Ham/Eggs/
```

### Synopsis

The main program can be invoked either through the `unicodecheck` command or through the Python main module option `python3 -m unicodecheck`.

```txt
usage: unicodecheck [-h] [-V] [-m {NFC,NFD,NFKC,NFKD}] [-d] [-u [NUMBER]] [-r] [-i] [-v]
                    PATH [PATH ...]
```

### Options

```txt
positional arguments:
  PATH                  specify an input file or directory (pass '-' to specify stdin)

options:
  -h, --help            show this help message and exit
  -V, --version         show program's version number and exit
  -m {NFC,NFD,NFKC,NFKD}, --mode {NFC,NFD,NFKC,NFKD}
                        target Unicode normalization (default: NFC)
  -d, --diff            show diffs between the original and normalized (default: False)
  -u [NUMBER], -U [NUMBER], --unified [NUMBER]
                        show unified diffs with NUMBER lines of context [NUMBER=3] (default: False)
  -r, --recursive       follow the directory tree rooted in each PATH argument (default: False)
  -i, --include-hidden  include hidden files and directories (default: False)
  -b PATTERN [PATTERN ...], --blacklist PATTERN [PATTERN ...]
                        notify if it contains PATTERN (case-sensitive) (default: None)
  -e, --error           return non-zero exit code on detection (default: False)
  -v, --verbose         report non-essential logs (default: False)
```

## Tips

### Check whether filenames are normalized

The `convmv` command is a good alternative to using this application.

#### NFC

```sh
convmv -f utf8 -t utf8 --nfc -r ./
```

#### NFD

```sh
convmv -f utf8 -t utf8 --nfd -r ./
```

## Notes

- This tool doesn't provide auto in-place (write) file normalization because Unicode normalization doesn't guarantee content equivalence.
- The procedure for determining binary files is based on Git's algorithm.

## License

MIT
ultimate_ai_labeller 0.1.4
AI Labelling tool for computer vision

# Ultimate AI Labeller

Desktop image annotation tool for object detection datasets (Tkinter + Ultralytics).

## Features

- Bounding-box annotation with drag, move, and resize handles
- Undo/redo history (`Ctrl+Z`, `Ctrl+Y`)
- Image navigation (`F` next/save, `D` previous)
- Auto red-region proposal (`A`)
- YOLO detection from UI (`Run Detection`)
- Model source selection:
  - Official bundled `yolo26n.pt`
  - Custom YOLO weights (`.pt`)
  - Custom RF-DETR weights (via Ultralytics interface)
- Auto-detect and propagate options
- Scrollable right settings panel
- Remove/restore bad frames from split
- Image dropdown jump
- Session resume (last project/split/image/model settings)
- English/Chinese UI switch and light/dark theme

## Dataset Structure

```text
your_project/
  images/
    train/
    val/
    test/
  labels/
    train/
    val/
    test/
```

- Image extensions: `.png`, `.jpg`, `.jpeg`
- Label format: YOLO txt (`class cx cy w h`, normalized)

Removed frames are moved to:

```text
your_project/
  removed/
    train|val|test/
      images/
      labels/
```

## Install

From PyPI:

```bash
pip install ultimate_ai_labeller
```

From local wheel:

```bash
pip install dist/ultimate_ai_labeller-0.1.4-py3-none-any.whl
```

From source:

```bash
pip install .
```

For development:

```bash
pip install -e .
```

## Run

```bash
ai-labeller
```

Or:

```bash
python src/ai_labeller/main.py
```

## Shortcuts

- `F`: save and next image
- `D`: previous image
- `A`: auto red detection
- `Ctrl+Z`: undo
- `Ctrl+Y`: redo
- `Delete`: delete selected box

## Notes

- Default detection model mode is `Official YOLO26n.pt (Bundled)`.
- The package includes `yolo26n.pt`, so first-run model download is not required.
- To use your own Tk app icon, put `app_icon.png` in `src/ai_labeller/assets/`.
- Session file: `~/.ai_labeller_session.json`.