semvec/pypi-packages huggingface dataset:
VIVA-RAHA1.1 0.1.1
A GUI application for image and video processing
Requires Python: >=3.6

# VIVA

VIVA is a graphical user interface (GUI) application built using FreeSimpleGUI and OpenCV. The application supports various image and video processing functionalities such as resizing images, converting videos to image frames, transforming images, and annotating images.

## Features

- **Resize Image:** Resizes an image while maintaining the aspect ratio.
- **Video to Image Converter:** Converts a video file to individual image frames.
- **Image Transformer:** Converts images to grayscale.
- **Annotate Images:** Allows annotation of images and saves the annotations in different formats with specified split ratios for training, validation, and testing.

## Requirements

- FreeSimpleGUI
- OpenCV
- Custom `gui` module

## Installation

Ensure you have the required libraries installed:

```bash
pip install FreeSimpleGUI opencv-python
```

Place the custom `gui` module in your project directory.

## Usage

Run the main script to start the application:

```bash
python main.py
```

## File Structure

- `main.py`: The main script that initializes and runs the GUI.
- `assets/`: Directory containing image assets used by the application.
- `frames/`: Directory where video frames are saved after conversion.

## Example

1. Resize an image:

```python
resized_image = gui.resize_image("V:/DATASTRUCT/VIVA/assets/annotated_bgi.png", 1100, 700)
cv2.imwrite("V:/DATASTRUCT/VIVA/assets/resized_bgi.png", resized_image)
```

2. Convert a video to image frames:

```python
gui.convert_video_to_images("path/to/video.mp4", "path/to/output/dir")
```

3. Convert images to grayscale:

```python
gui.convert_images_to_grayscale("path/to/image/folder")
```

4. Annotate images and save annotations:

```python
annotations = gui.annotation_tool(image_paths)
gui.save_annotations(annotations, format_choice, (train_ratio, val_ratio, test_ratio))
```

## Contributing

Feel free to contribute to this project by opening issues or submitting pull requests.

## License

This project is licensed under the MIT License.
VIVA-RAHA1 0.1.0
A GUI application for image and video processing
Requires Python: >=3.6

# VIVA

VIVA is a graphical user interface (GUI) application built using FreeSimpleGUI and OpenCV. The application supports various image and video processing functionalities such as resizing images, converting videos to image frames, transforming images, and annotating images.

## Features

- **Resize Image:** Resizes an image while maintaining the aspect ratio.
- **Video to Image Converter:** Converts a video file to individual image frames.
- **Image Transformer:** Converts images to grayscale.
- **Annotate Images:** Allows annotation of images and saves the annotations in different formats with specified split ratios for training, validation, and testing.

## Requirements

- FreeSimpleGUI
- OpenCV
- Custom `gui` module

## Installation

Ensure you have the required libraries installed:

```bash
pip install FreeSimpleGUI opencv-python
```

Place the custom `gui` module in your project directory.

## Usage

Run the main script to start the application:

```bash
python main.py
```

## File Structure

- `main.py`: The main script that initializes and runs the GUI.
- `assets/`: Directory containing image assets used by the application.
- `frames/`: Directory where video frames are saved after conversion.

## Example

1. Resize an image:

```python
resized_image = gui.resize_image("V:/DATASTRUCT/VIVA/assets/annotated_bgi.png", 1100, 700)
cv2.imwrite("V:/DATASTRUCT/VIVA/assets/resized_bgi.png", resized_image)
```

2. Convert a video to image frames:

```python
gui.convert_video_to_images("path/to/video.mp4", "path/to/output/dir")
```

3. Convert images to grayscale:

```python
gui.convert_images_to_grayscale("path/to/image/folder")
```

4. Annotate images and save annotations:

```python
annotations = gui.annotation_tool(image_paths)
gui.save_annotations(annotations, format_choice, (train_ratio, val_ratio, test_ratio))
```

## Contributing

Feel free to contribute to this project by opening issues or submitting pull requests.

## License

This project is licensed under the MIT License.
oxen_pyo3 0.1.3
Add your description here
Requires Python: >=3.11

# Oxen-Pyo3
一个用于 Oxen Rust 库的 Python 封装。

## 安装
```
pip install package/oxen_pyo3-0.1.1-cp312-cp312-manylinux_2_34_x86_64.whl
```

## 使用

书写因子逻辑, 请参考 [factor_example.py](factor_example.py), 然后测试因子直接执行 [factor_engine_demo.py](factor_engine_demo.py) 即可.

```bash
uv run factor_engine_demo.py
```

## 开发环境
```bash
# 安装uv虚拟环境
curl -LsSf https://astral.sh/uv/install.sh | sh
# 同步环境
uv sync
# 进入虚拟环境
source .venv/bin/activate

# 参考src/lib.rs编写绑定函数
# 根据lib.rs编写pyi文件, 可以用GPT生成

# 调试编译, 会安装到当前虚拟环境
maturin develop --uv
# 生产编译, 会在target文件夹中生成wheels文件
maturin develop --release --uv

注意, 重新编译前需要清理缓存文件, 可直接执行build.sh
```
VIVA-RAHA 0.1.0
A GUI application for image and video processing
Requires Python: >=3.6

# VIVA

VIVA is a graphical user interface (GUI) application built using FreeSimpleGUI and OpenCV. The application supports various image and video processing functionalities such as resizing images, converting videos to image frames, transforming images, and annotating images.

## Features

- **Resize Image:** Resizes an image while maintaining the aspect ratio.
- **Video to Image Converter:** Converts a video file to individual image frames.
- **Image Transformer:** Converts images to grayscale.
- **Annotate Images:** Allows annotation of images and saves the annotations in different formats with specified split ratios for training, validation, and testing.

## Requirements

- FreeSimpleGUI
- OpenCV
- Custom `gui` module

## Installation

Ensure you have the required libraries installed:

```bash
pip install FreeSimpleGUI opencv-python
```

Place the custom `gui` module in your project directory.

## Usage

Run the main script to start the application:

```bash
python main.py
```

## File Structure

- `main.py`: The main script that initializes and runs the GUI.
- `assets/`: Directory containing image assets used by the application.
- `frames/`: Directory where video frames are saved after conversion.

## Example

1. Resize an image:

```python
resized_image = gui.resize_image("V:/DATASTRUCT/VIVA/assets/annotated_bgi.png", 1100, 700)
cv2.imwrite("V:/DATASTRUCT/VIVA/assets/resized_bgi.png", resized_image)
```

2. Convert a video to image frames:

```python
gui.convert_video_to_images("path/to/video.mp4", "path/to/output/dir")
```

3. Convert images to grayscale:

```python
gui.convert_images_to_grayscale("path/to/image/folder")
```

4. Annotate images and save annotations:

```python
annotations = gui.annotation_tool(image_paths)
gui.save_annotations(annotations, format_choice, (train_ratio, val_ratio, test_ratio))
```

## Contributing

Feel free to contribute to this project by opening issues or submitting pull requests.

## License

This project is licensed under the MIT License.