Jcy-utils 0.0.3

A collection of image processing utilities for splitting, concatenation, and metrics calculation.

Jcy_utils

A comprehensive Python utility library for image processing, file management, and metric calculations.

📦 Installation

pip install Jcy_utils

🚀 Features

• Image Manipulation: Split images, add text, pad to square, resize proportionally, and concatenate images.
• Batch Processing: Recursively process directories with progress bars.
• Metrics: Calculate Precision, Recall, TP, FP, etc., for classification tasks.
• Utilities: Retry decorators, file copying tools.

📖 Usage Examples

1. Add Text to Image

from Jcy_utils import add_text_to_image

add_text_to_image(
    input_path="input.jpg",
    output_path="output.jpg",
    text="Sample Text",
    position=(50, 50),
    color=(255, 0, 0) # Red
)

2. Concatenate Images

Combine multiple images into a grid layout automatically.

from Jcy_utils import concat_images_list_with_padding_rowmax

images = ["img1.jpg", "img2.jpg", "img3.jpg", "img4.jpg"]
concat_images_list_with_padding_rowmax(
    images, 
    target_size=512, 
    save_path="grid_result.jpg", 
    max_images_per_row=2
)

3. Batch Directory Processing

Apply a custom function to every image in a folder structure.

from Jcy_utils import wrap_dir

def my_process(input_path, output_path):
    # Your custom logic here
    pass

wrap_dir(
    func=my_process,
    in_dir="./data/source",
    out_dir="./data/processed",
    ext=['jpg', 'png'],
    level=0  # 0 means auto-detect depth
)

4. Calculate Metrics

Compute Precision/Recall by comparing Ground Truth (GT) and Prediction dictionaries.

from Jcy_utils import calculate_pr2

gt = {'img1': 1, 'img2': 0, 'img3': 1}
pred = {'img1': 1, 'img2': 1, 'img3': 0}

metrics = calculate_pr2(gt, pred)
print(f"Precision: {metrics['precision']:.2f}, Recall: {metrics['recall']:.2f}")

5. Resize Image by Max Side

Resize an image proportionally so its longest dimension matches the target size.

import cv2
from Jcy_utils import resize_by_maxside

# Read image using OpenCV
img = cv2.imread("input.jpg")

# Resize so the longest side is 512 pixels
resized_img = resize_by_maxside(img, max_side=512)

# Save the result
cv2.imwrite("resized_512.jpg", resized_img)

📦 How to Publish to PyPI

If you are the maintainer of this library, follow these steps to publish a new version to PyPI.

1. Prerequisites

Ensure you have the build tools installed:

pip install --upgrade build twine

2. Update Version

Modify the version string in pyproject.toml and src/Jcy_utils/__init__.py (e.g., change 0.0.1 to 0.0.2).

3. Build the Package

Run the following command in the project root directory:

python -m build

This will generate distribution files in the dist/ folder.

4. Upload to PyPI

Upload the newly built packages using Twine:

twine upload dist/*

You will be prompted for your PyPI API token (username: __token__).

🛠 Dependencies

• numpy
• opencv-python
• Pillow
• tqdm

📄 License

MIT License