https://github.com/serpentbit/ovl
🦉 Python Module for real-time computer vision pipelines
https://github.com/serpentbit/ovl
computer-vision first first-robotics-competition image-processing object-detection opencv opencv-python ovl pipeline python robotics
Last synced: 3 months ago
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🦉 Python Module for real-time computer vision pipelines
- Host: GitHub
- URL: https://github.com/serpentbit/ovl
- Owner: SerpentBit
- License: other
- Created: 2018-12-03T18:17:05.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2023-02-20T13:19:14.000Z (almost 3 years ago)
- Last Synced: 2025-01-30T23:51:12.644Z (12 months ago)
- Topics: computer-vision, first, first-robotics-competition, image-processing, object-detection, opencv, opencv-python, ovl, pipeline, python, robotics
- Language: Python
- Homepage:
- Size: 1.17 MB
- Stars: 8
- Watchers: 3
- Forks: 4
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
- Changelog: changelogs/0.2.5.2_to_2020.1.1
- License: LICENSE
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README
# OVL - Object Vision Library
Python Module for Computer Vision Object Tracking and Detection mainly for the FIRST® 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](https://github.com/1937Elysium/Ovl-Python/tree/master/changelogs)*
## Documentation
There are multiple code examples [here](https://github.com/1937Elysium/Ovl-Python/tree/master/code%20examples)
Documentation is available [here](https://ovl.readthedocs.io/)
### 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+
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.
> `python -m pip install ovl`
## 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](https://github.com/1937Elysium/Ovl-Python/tree/master/code%20examples)