Skip to main content

Detects numeric displays in images using OpenCV

Project description


A Python 3 package for detecting numeric seven-segment displays in images and running perspective correction on them using OpenCV 4.

detect_box_sequences() first applies a series of filters to the input image to reduce noise, bring out primary contours and bridge gaps between digit segments (see images.apply_filters()). Next, all resulting contours are analyzed by comparing their geometric properties to a set of criteria which define what it means for a contour to resemble a seven-segment digit. Lots of assumptions are being made here (see config.cfg). A contour resembling a seven-segment digit is used to instantiate a Box object. Several boxes lined up in a row make up a box Sequence. Sequences are contained in a Bag.

In other words, raw contours serve as input for an object detection pipeline which produces results in the form of a crawlable object tree.


$ brew install opencv
$ pip install numericvision

Using the package

from numericvision import detect_box_sequences

box_sequences = detect_box_sequences("image.jpg")

Running from the command line

$ python -m numericvision image.jpg

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

numericvision-0.1.0.tar.gz (11.6 kB view hashes)

Uploaded source

Built Distribution

numericvision-0.1.0-py3-none-any.whl (16.5 kB view hashes)

Uploaded py3

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