Skip to main content

OVL - Object Vision Library

OVL Logo

Python Module for Computer Vision Object Tracking and Detection mainly for the FIRSTֲ® Robotics Competition Program

Ovl support complex yet modular computer vision pipelines that are easy to create and modify.

Easy to create and setup for beginners and flexible for pros

You can follow up on changes in for the current version in the changelog folder

Documentation

There are multiple code examples here

Documentation is available here

Dependencies:

The following python module dependencies are needed:

  • OpenCV

  • numpy

The following python modules are optional for certain features:

  • NetworkTables (pyNetworkTables) for NetworkTableConnection (installed automatically)

OVL is officially supported for python 3.7+ only!

Installation:

Using pip:
python -m pip install ovl[cv]

For the full installation of all features use: python -m pip install ovl[full]

For the frc related features use the frc option: python -m pip install ovl[frc]

Note that ovl doesn't come with the precompiled version of opencv for python automatically. If you wish to compile opencv for yourself - simply refrain from using the cv flag during installation.

Usage:

The library uses simple yet highly customizable syntax to create a vision pipeline using the Vision object

A pipeline that detects a yellow circle:

import ovl

target_filters = [ovl.percent_area_filter(min_area=0.005),
                  ovl.circle_filter(min_area_ratio=0.7),
                  ovl.area_sort()]

threshold = ovl.Color([20, 100, 100], [55, 255, 255])

yellow_circle = ovl.Vision(threshold=threshold,
                           target_filters=target_filters,
                           camera=0,  # open the first connected camera
                           image_filters=[ovl.gaussian_blur()])

while True:
    image = yellow_circle.get_image()
    targets, filtered_image = yellow_circle.detect(image)
    directions = yellow_circle.get_directions(targets, filtered_image)

    print(directions)  # prints out the (x, y) coordinates of the largest target


There are more code examples and usages here

Metadata

Release files for ovl 2022.2.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for ovl 2022.2.2
File Size Uploaded Provenance Actions
ovl-2022.2.2.tar.gz 50.7 kB Without provenance Details for ovl-2022.2.2.tar.gz

Release files / ovl-2022.2.2.tar.gz

Download URL ovl-2022.2.2.tar.gz
Size 50.7 kB
Tags Source
SHA-256 checksum
How to use checksums
5dad10f4a4d296760b8453f066d4c48b2fb32faefb27d85b0b14a74305e5b130
BLAKE2b-256 checksum
How to use checksums
4bbf3c5bc07a36740b4dacba3b9721e5a16101d4ae009a84677e18835034e6aa
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/40.6.2 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.2

Security for ovl 2022.2.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

2022.2.2 This release

1 release file No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page