Skip to main content

Light Weight Toolkit for Bounding Boxes

Project description

PyBboxes

Python versions Total downloads Monthly downloads
Python versions DOI Python versions

Light weight toolkit for bounding boxes providing conversion between bounding box types and simple computations. Supported bounding box types (italicized text indicates normalized values):

  • albumentations : Albumentations Format
    • [x-tl, y-tl, x-br, y-br] (Normalized VOC Format) Top-left coordinates & Bottom-right coordinates
  • coco : COCO (Common Objects in Context)
    • [x-tl, y-tl, w, h] Top-left corner & width & height
  • fiftyone : FiftyOne
    • [x-tl, y-tl, w, h] (Normalized COCO Format) Top-left coordinates & width & height
  • voc : Pascal VOC
    • [x-tl, y-tl, x-br, y-br] Top-left coordinates & Bottom-right coordinates
  • yolo : YOLO
    • [x-c, y-c, w, h] Center coordinates & width & height

Glossary

  • tl: top-left
  • br: bottom-right
  • h: height
  • w: width
  • c: center

Important Notice

Support for Python<3.8 will be dropped starting version 0.2 though the development for Python3.6 and Python3.7 may continue where it will be developed under version 0.1.x for future versions. This may introduce; however, certain discrepancies and/or unsupported operations in the 0.1.x versions. To fully utilize and benefit from the entire package, we recommend using Python3.8 at minimum (Python>=3.8).

Installation

Through pip (recommended),

pip install pybboxes

or build from source,

git clone https://github.com/devrimcavusoglu/pybboxes.git
cd pybboxes
python setup.py install

Bounding Boxes

You can easily create bounding box as easy as

from pybboxes import BoundingBox

my_coco_box = [98, 345, 322, 117]
coco_bbox = BoundingBox.from_coco(*my_coco_box)  # <[98 345 322 117] (322x117) | Image: (?x?)>
# or alternatively
# coco_bbox = BoundingBox.from_array(my_coco_box)

Out of Bounds Boxes

Pybboxes supports OOB boxes, there exists a keyword strict in both Box classes (construction) and in functional modules. When strict=True, it does not allow out-of-bounds boxes to be constructed and raises an exception, while it does allow out-of-bounds boxes to be constructed and used when strict=False. Also, there is a property is_oob that indicates whether a particular bouding box is OOB or not.

Important Note that, if the return value for is_oob is None, then it indicates that OOB status is unknown (e.g. image size required to determine, but not given). Thus, values None and False indicates different information.

from pybboxes import BoundingBox

image_size = (640, 480)
my_coco_box = [98, 345, 580, 245]  # OOB box for 640x480
coco_bbox = BoundingBox.from_coco(*my_coco_box, image_size=image_size)  # Exception
# ValueError: Given bounding box values is out of bounds. To silently skip out of bounds cases pass 'strict=False'.

coco_bbox = BoundingBox.from_coco(*my_coco_box, image_size=image_size, strict=False)  # No Exception
coco_bbox.is_oob  # True

If you want to allow OOB, but still check OOB status, you should use strict=False and is_oob where needed.

Conversion

With the BoundingBox class the conversion is as easy as one method call.

from pybboxes import BoundingBox

my_coco_box = [98, 345, 322, 117]
coco_bbox = BoundingBox.from_coco(*my_coco_box)  # <[98 345 322 117] (322x117) | Image: (?x?)>
voc_bbox = coco_bbox.to_voc()  # <[98 345 420 462] (322x117) | Image: (?x?)>
voc_bbox_values = coco_bbox.to_voc(return_values=True)  # (98, 345, 420, 462)

However, if you try to make conversion between two bounding boxes that require scaling/normalization it'll give an error

from pybboxes import BoundingBox

my_coco_box = [98, 345, 322, 117]
coco_bbox = BoundingBox.from_coco(*my_coco_box)  # <[98 345 322 117] (322x117) | Image: (?x?)>
# yolo_bbox = coco_bbox.to_yolo()  # this will raise an exception

# You need to set image_size for coco_bbox and then you're good to go
coco_bbox.image_size = (640, 480)
yolo_bbox = coco_bbox.to_yolo()  # <[0.4047 0.8406 0.5031 0.2437] (322x117) | Image: (640x480)>

Image size associated with the bounding box can be given at the instantiation or while using classmethods e.g from_coco().

from pybboxes import BoundingBox

my_coco_box = [98, 345, 322, 117]
coco_bbox = BoundingBox.from_coco(*my_coco_box, image_size=(640, 480))  # <[98 345 322 117] (322x117) | Image: (640x480)>
# no longer raises exception
yolo_bbox = coco_bbox.to_yolo()  # <[0.4047 0.8406 0.5031 0.2437] (322x117) | Image: (640x480)> 

Box operations

Box operations now available as of v0.1.0.

from pybboxes import BoundingBox

my_coco_box = [98, 345, 322, 117]
my_coco_box2 = [90, 350, 310, 122]
coco_bbox = BoundingBox.from_coco(*my_coco_box, image_size=(640, 480))
coco_bbox2 = BoundingBox.from_coco(*my_coco_box2, image_size=(640, 480))

iou = coco_bbox.iou(coco_bbox2)  # 0.8117110631149508
area_union = coco_bbox + coco_bbox2  # 41670 | alternative way: coco_bbox.union(coco_bbox2)
total_area = coco_bbox.area + coco_bbox2.area  # 75494  (not union)
intersection_area = coco_bbox * coco_bbox2  # 33824 | alternative way: coco_bbox.intersection(coco_bbox2)
first_bbox_diff = coco_bbox - coco_bbox2  # 3850
second_bbox_diff = coco_bbox2 - coco_bbox  # 3996
bbox_ratio = coco_bbox / coco_bbox2 # 0.9961396086726599 (not IOU)

Functional

Note: functional computations are moved under pybboxes.functional starting with the version 0.1.0. The only exception is that convert_bbox() which still can be used by importing pybboxes only (for backward compatibility).

Conversion

You are able to convert from any bounding box type to another.

import pybboxes as pbx

coco_bbox = (1,2,3,4)  # COCO Format bbox as (x-tl,y-tl,w,h)
voc_bbox = (1,2,3,4)  # Pascal VOC Format bbox as (x-tl,y-tl,x-br,y-br)
pbx.convert_bbox(coco_bbox, from_type="coco", to_type="voc")  # (1, 2, 4, 6)
pbx.convert_bbox(voc_bbox, from_type="voc", to_type="coco")  # (1, 2, 2, 2)

Some formats require image width and height information for scaling, e.g. YOLO bbox (resulting coordinates are rounded to 2 decimals to ease reading).

import pybboxes as pbx

voc_bbox = (1,2,3,4)  # Pascal VOC Format bbox as (x-tl,y-tl,x-br,y-br)
pbx.convert_bbox(voc_bbox, from_type="voc", to_type="yolo", image_size=(28, 28))  # (0.07, 0.11, 0.07, 0.07)

Computation

You can also make computations on supported bounding box formats.

import pybboxes.functional as pbf

coco_bbox = (1,2,3,4)  # COCO Format bbox as (x-tl,y-tl,w,h)
voc_bbox = (1,2,3,4)  # Pascal VOC Format bbox as (x-tl,y-tl,x-br,y-br)
pbf.compute_area(coco_bbox, bbox_type="coco")  # 12
pbf.compute_area(voc_bbox, bbox_type="voc")  # 4

Contributing

Installation

Install the package as follows, which will set you ready for the development mode.

pip install -e .[dev]

Tests

To tests simply run.

python tests/run_tests.py

Code Style

To check code style,

python tests/run_code_style.py check

To format codebase,

python tests/run_code_style.py format

License

Licensed under the MIT License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pybboxes-0.1.6.tar.gz (19.0 kB view hashes)

Uploaded Source

Built Distribution

pybboxes-0.1.6-py3-none-any.whl (24.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page