easy-bbox 1.0.5
A lightweight and easy bounding box manipulation library with Pascal VOC, COCO, and YOLO format conversions.
License: MIT
Requires Python: >=3.9
Keywords: bounding-box, bbox, computer-vision, image-processing, object-detection, yolo, coco, pascal-voc, IoU

# Easy Bbox

<p align="center">
    <a href="https://pypi.org/project/easy-bbox"><img alt="Package version" src="https://img.shields.io/pypi/v/easy-bbox.svg"></a>
    <a href="https://github.com/Alex-experiments/easy-bbox/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/badge/License-MIT-yellow.svg"></a>
    <a href="https://github.com/Alex-experiments/easy-bbox/actions"><img alt="Coverage" src="https://Alex-experiments.github.io/easy-bbox/badges/coverage.svg"></a>
    <a href="https://alex-experiments.github.io/easy-bbox"><img alt="Documentation" src="https://img.shields.io/badge/Documentation-gh--pages-blue"></a>
</p>


Easy Bbox is a Python package designed to simplify bounding box operations. It provides a comprehensive set of tools for manipulating bounding boxes in various coordinate formats, including Pascal VOC, COCO, YOLO and Albumentations. The package supports transformations, geometric operations, and conversions, making it a versatile tool for computer vision tasks.

## Features
- **Pydantic model**: Bbox objects are Pydantic models.
- **Multiple Coordinate Formats**: Supports Pascal VOC, COCO, YOLO and Albumentation formats.
- **Transformations**: Shift, scale, expand, and pad bounding boxes.
- **Geometric Operations**: Calculate intersections, unions, and IoU (Intersection over Union).
- **Conversions**: Convert between different coordinate formats.
- **Utility Functions**: Includes Non-Maximum Suppression (NMS) for filtering overlapping bounding boxes.

## Installation
Easy Bbox is published as a python package and can be pip installed.

```bash
pip install easy-bbox
```

## Usage
### Creating a Bounding Box
You can create a bounding box using the `Bbox` class. The bounding box is stored in Pascal VOC format, which is top-left, bottom-right with a top-left origin (PIL coordinate system), but can be instantiated from different formats.

```py
from easy_bbox import Bbox

# All of the following Bbox are equal

# Create a bounding box using top-left and bottom-right coordinates
bbox = Bbox(left=10, top=20, right=30, bottom=40)

# Instantiate from a sequence in Pascal VOC format
bbox = Bbox.from_pascal_voc([10, 20, 30, 40])  
bbox = Bbox.from_tlbr([10, 20, 30, 40])   
bbox = Bbox.from_xyxy([10, 20, 30, 40])  
bbox = Bbox.from_list([10, 20, 30, 40])

# Create a bounding box using top-left and width-height coordinates (COCO format)
bbox = Bbox.from_tlwh((10, 20, 20, 20))
bbox = Bbox.from_coco((10, 20, 20, 20))

# Create a bounding box using center and width-height coordinates
bbox = Bbox.from_cwh((20, 30, 20, 20))
```

### Transformations
Easy Bbox provides several methods for transforming bounding boxes:

![bbox_transformations](https://raw.githubusercontent.com/Alex-experiments/easy-bbox/main/images/bbox_transformations.png)

### Conversions
Easy Bbox provides methods for converting between different coordinate formats:

```py
# Convert to Top-Left, Bottom-Right format
tlbr = bbox.to_tlbr() # Same as `.to_pascal_voc()`, `.to_xyxy()`

# Convert to Top-Left, Width-Height format
tlwh = bbox.to_tlwh()   # Same as `.to_coco()`

# Convert to Center, Width-Height format
cwh = bbox.to_cwh()

# Convert to normalized Top-Left, Bottom-Right format
norm_tlbr = bbox.to_norm_tlbr(img_w=100, img_h=100) # Same as `.to_albu(...)`

# Convert to normalized Top-Left, Width-Height format
norm_tlwh = bbox.to_norm_tlwh(img_w=100, img_h=100)

# Convert to normalized Center, Width-Height format
norm_cwh = bbox.to_norm_cwh(img_w=100, img_h=100) # Same as `.to_yolo(...)`

# Convert to polygon format
polygon = bbox.to_polygon()
```

### Utility 
Easy Bbox includes utility functions for common tasks:

![bbox_utils](https://raw.githubusercontent.com/Alex-experiments/easy-bbox/main/images/bbox_utils.png)

```py
from easy_bbox import nms

# Get the minimal englobing bbox
union = bbox1.union(bbox2) # same as bbox1 | bbox2

# Get the intersection
inter = bbox1.intersection(bbox2) # same as bbox1 & bbox2

# Calculate the IoU of two bboxes
iou = bbox1.iou(bbox2)

# Check if two bboxes are overlapping
overlap = bbox1.overlaps(bbox2)

# Check if a bbox contains a point
is_inside = bbox1.contains_point((5, 10))

# Calculate the distance from a point to a bbox
dist = bbox1.distance_to_point((5, 10))

# Perform Non-Maximum Suppression
selected_bboxes = nms(bboxes, scores, iou_threshold=0.5)
```