https://github.com/alkasm/colorfilters

Image thresholding in multiple colorspaces.
https://github.com/alkasm/colorfilters

computer-vision image-processing opencv

Last synced: 18 days ago
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Image thresholding in multiple colorspaces.

• Host: GitHub
• URL: https://github.com/alkasm/colorfilters
• Owner: alkasm
• License: mit
• Created: 2017-06-11T05:05:47.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2021-10-25T06:13:12.000Z (about 3 years ago)
• Last Synced: 2024-10-12T16:27:26.420Z (about 1 month ago)
• Topics: computer-vision, image-processing, opencv
• Language: Python
• Homepage:
• Size: 967 KB
• Stars: 100
• Watchers: 3
• Forks: 20
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# colorfilters

Threshold your images in any colorspace!

* BGR (RGB)

* HSV

* HLS (HSL)

* Lab (CIELAB/L\*a\*b\*)

* Luv (L\*u\*v\*)

* YCrCb (YCbCr/YCC)

* XYZ (CIEXYZ)

* Grayscale (single channel)

![Example Image](readme-example.png)

## Getting Started

Install into a Python virtual environment, as you would any other Python project.

```sh

$ python3 -m venv venv

$ source venv/bin/activate

(venv) $ pip install git+https://github.com/alkasm/colorfilters

```

Run the module as a script on any image you want:

```sh

(venv) $ python3 -m colorfilters path/to/image.png hsv

```

## Usage

As a script, just run the module directly as above. You can always check the `--help` flag when running the module as a script for more info:

```sh

(venv) $ python3 -m colorfilters --help

usage: test color thresholding of images in different colorspaces

       [-h] image {bgr,hsv,hls,lab,luv,ycc,xyz,gray}

positional arguments:

  image                 path to image

  {bgr,hsv,hls,lab,luv,ycc,xyz,gray}

                        colorspace to filter in

optional arguments:

  -h, --help            show this help message and exit

```

Use inside your own Python projects:

```python

>>> from colorfilters import HSVFilter

>>> import cv2 as cv

>>> 

>>> img = cv.imread("lane.jpg")

>>> window = HSVFilter(img)

>>> window.show()

>>> 

>>> print(f"Image filtered in HSV between {window.lowerb} and {window.upperb}.")

Image filtered in HSV between [51, 0, 183] and [63, 255, 255].

```

The window object has a few properties you might be interested in after successfully filtering your image:

```python

>>> window.lowerb     # lower bound used for cv.inRange()

>>> window.upperb     # upper bound used for cv.inRange()

>>> window.mask       # mask from cv.inRange()

>>> window.masked     # image with mask applied

>>> window.img        # image input into the window

>>> window.converted  # image converted into the corresponding colorspace

```