semvec/pypi-packages huggingface dataset:
visionviz 0.1.0
Visualization tools for computer vision applications
Requires Python: >=3.8

# VisionViz

Visualization tools for computer vision applications by Intel Open Edge Platform.

## Installation

Using uv (recommended):

```bash
uv pip install visionviz
```

Using pip:

```bash
pip install visionviz
```

## Usage

```python
import visionviz

# Add usage examples here
```

## Development

To set up the development environment:

1. Install uv:

   ```bash
   curl -LsSf https://astral.sh/uv/install.sh | sh
   ```

2. Clone the repository:

   ```bash
   git clone https://github.com/intel/visionai.git
   cd visionai
   ```

3. Create and activate a virtual environment:

   ```bash
   uv venv
   source .venv/bin/activate  # On Unix/macOS
   # or
   .venv\Scripts\activate  # On Windows
   ```

4. Install development dependencies:

   ```bash
   uv pip install -e ".[dev]"
   ```

## License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

## Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for more details.
visiontune 0.1.0
Tuning tools for computer vision models
Requires Python: >=3.8

# VisionTune

Tuning tools for computer vision models by Intel Open Edge Platform.

## Installation

Using uv (recommended):

```bash
uv pip install visiontune
```

Using pip:

```bash
pip install visiontune
```

## Usage

```python
import visiontune

# Add usage examples here
```

## Development

To set up the development environment:

1. Install uv:

   ```bash
   curl -LsSf https://astral.sh/uv/install.sh | sh
   ```

2. Clone the repository:

   ```bash
   git clone https://github.com/intel/visionai.git
   cd visionai
   ```

3. Create and activate a virtual environment:

   ```bash
   uv venv
   source .venv/bin/activate  # On Unix/macOS
   # or
   .venv\Scripts\activate  # On Windows
   ```

4. Install development dependencies:

   ```bash
   uv pip install -e ".[dev]"
   ```

## License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

## Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for more details.
visionmonitor 0.1.0
Monitoring tools for computer vision applications
Requires Python: >=3.8

# VisionMonitor

Monitoring tools for computer vision applications by Intel Open Edge Platform.

## Installation

Using uv (recommended):

```bash
uv pip install visionmonitor
```

Using pip:

```bash
pip install visionmonitor
```

## Usage

```python
import visionmonitor

# Add usage examples here
```

## Development

To set up the development environment:

1. Install uv:

   ```bash
   curl -LsSf https://astral.sh/uv/install.sh | sh
   ```

2. Clone the repository:

   ```bash
   git clone https://github.com/intel/visionai.git
   cd visionai
   ```

3. Create and activate a virtual environment:

   ```bash
   uv venv
   source .venv/bin/activate  # On Unix/macOS
   # or
   .venv\Scripts\activate  # On Windows
   ```

4. Install development dependencies:

   ```bash
   uv pip install -e ".[dev]"
   ```

## License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

## Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for more details.
visioninfer 0.1.0
Inference tools for computer vision models
Requires Python: >=3.8

# VisionInfer

Inference tools for computer vision models by Intel Open Edge Platform.

## Installation

Using uv (recommended):

```bash
uv pip install visioninfer
```

Using pip:

```bash
pip install visioninfer
```

## Usage

```python
import visioninfer

# Add usage examples here
```

## Development

To set up the development environment:

1. Install uv:

   ```bash
   curl -LsSf https://astral.sh/uv/install.sh | sh
   ```

2. Clone the repository:

   ```bash
   git clone https://github.com/intel/visionai.git
   cd visionai
   ```

3. Create and activate a virtual environment:

   ```bash
   uv venv
   source .venv/bin/activate  # On Unix/macOS
   # or
   .venv\Scripts\activate  # On Windows
   ```

4. Install development dependencies:

   ```bash
   uv pip install -e ".[dev]"
   ```

## License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

## Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for more details.
visiondata 0.1.0
Data management and processing tools for computer vision applications
Requires Python: >=3.8

# VisionData

Data management and processing tools for computer vision applications by Intel Open Edge Platform.

## Installation

Using uv (recommended):

```bash
uv pip install visiondata
```

Using pip:

```bash
pip install visiondata
```

## Usage

```python
import visiondata

# Add usage examples here
```

## Development

To set up the development environment:

1. Install uv:

   ```bash
   curl -LsSf https://astral.sh/uv/install.sh | sh
   ```

2. Clone the repository:

   ```bash
   git clone https://github.com/intel/visionai.git
   cd visionai
   ```

3. Create and activate a virtual environment:

   ```bash
   uv venv
   source .venv/bin/activate  # On Unix/macOS
   # or
   .venv\Scripts\activate  # On Windows
   ```

4. Install development dependencies:

   ```bash
   uv pip install -e ".[dev]"
   ```

## License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

## Contributing

We welcome contributions! Please see our [Contributing Guide](CONTRIBUTING.md) for more details.
topovec 0.1.3
Visualizer of 3d vector field with accent of topological solitons.
Requires Python: >=3.10
Keywords: liquid crystal, magnetization, physics, soliton, topology, visualization

# TopoVec

## Installation

### Prerequisites

We recommend to Install [UV](https://docs.astral.sh/uv/) package manager according to the [manual](https://docs.astral.sh/uv/getting-started/installation/).

### Normal installation

If only GUI or scripts are going to be used, `topovec` can be installed as a tool.
E.g. using [UV](https://docs.astral.sh/uv/)

```sh
uvx tool install topovec
```

or using [pipx](https://github.com/pypa/pipx):

```sh
pipx install topovec
```

To use `topovec` in [jupter](https://jupyter.org/) or [marimo](https://github.com/marimo-team/marimo) notebook,
we suggest to use virtual environment.
UV provides very convenient way to proceed.
First create directory for you project:

```sh
uv init <your_project>
```

Then enter into the just create folder and install `topovec`:

```sh
cd <your_project>
uv add topovec
```

Most functionality of `topovec` are in plugins.
All the plugins can be installed using

```sh
uv add topovec --all-extras
```

Now you can start notebook as described [below](#First-steps).

### For development

Clone or download the repository:

```sh
git clone https://gitlab.com/alepoydes/topovec.git
```

Switch to the newly created directory:

```sh
cd topovec
```

Run UV to create virtual environment and install the library.

```sh
uv sync --all-extras
```

Most of the functionality are provided by plugins which have dependencies on external packages.
`--all-extras` will install all dependencies, which may lead to long installation time 
or incompatibilities with already installed software.
You can select which plugins to choose using `--extra` key.
For example, if we are interested only in OpenGL functionality, we can install only `mgl` plugin.

```sh
uv sync --extra mgl
```

## First steps

It is convenient to prepare plots for publication in a notebook.
To run [Jupter](https://jupyter.org/) Lab inside the environment associated with `topovec`,
run in the `topovec` folder the following command:

```sh
uv run --with jupyter jupyter lab
```

Demonstration of basic functionality of the library can be found in the notebook
[notebooks/demo1.ipynb](notebooks/demo1.ipynb).