semvec/pypi-packages huggingface dataset:
WSI-Preprocessing 0.1.0
A package for extracting image patches from SVS files and performing color normalization
License: MIT
Requires Python: >=3.6

# WSI_Preprocessing

This package provides functionalities for extracting image patches from SVS files and performing color normalization on images.

## Installation

To install this package, use:

```sh
pip install WSI_Preprocessing
```

## Usage

### Key Verification

To use this package, you will need to input a key for verification. When you run the functions from this package, you will be prompted to enter the key. Ensure you have the correct key to proceed.

### Extract Patches
To extract patches from SVS files, use the process_svs_files function:

```sh
from WSI_Preprocessing import process_svs_files

# Define the paths
base_path = 'path/to/your/svs/files'
output_base = 'path/to/output/folder'
threshold = 50  # Saturation threshold for saving patches
patch_size = 512  # Size of the patches
target_magnification = 20  # Target magnification level

# Process SVS files to extract patches
process_svs_files(base_path, output_base, saturation_threshold=threshold, patch_size=patch_size, target_magnification=target_magnification)
```

### Normalize Images

To normalize images using a reference image, use the normalize_images function:
```sh
from WSI_Preprocessing import normalize_images

# Define the paths
input_folder = 'path/to/your/input/images'
reference_image_path = 'path/to/your/reference/image.png'
output_folder = 'path/to/output/folder'

# Normalize images
normalize_images(input_folder, reference_image_path, output_folder)
```

### Example
Here is a complete example of how to use both functionalities:

1、Extract patches from SVS files and save them to a specified directory.

2、Normalize the extracted patches using a reference image.

```sh
from WSI_Preprocessing import process_svs_files, normalize_images

# Step 1: Extract patches
base_path = 'path/to/your/svs/files'
output_base = 'path/to/output/folder'
threshold = 50  # Saturation threshold for saving patches
patch_size = 512  # Size of the patches
target_magnification = 20  # Target magnification level

process_svs_files(base_path, output_base, saturation_threshold=threshold, patch_size=patch_size, target_magnification=target_magnification)

# Step 2: Normalize the extracted patches
input_folder = 'path/to/output/folder'
reference_image_path = 'path/to/your/reference/image.png'
output_folder = 'path/to/normalized/output/folder'

normalize_images(input_folder, reference_image_path, output_folder)
```

## Contributing

If you would like to contribute to this package, please fork the repository and submit a pull request. For major changes, please open an issue first to discuss what you would like to change.

## License
This project is licensed under the MIT License.