This Python script loads an aerial image and converts it to the HSV color space. It then defines a range of colors considered "brown" in the HSV space and creates a binary mask that selects only those colors. Finally, it changes the color of the pixels selected by the mask to Red and saves the resulting image to a file.
HSV stands for Hue, Saturation, and Value. It is a color space often used in image processing and computer vision because it separates the color information from the brightness information, making it easier to segment and analyze objects based on their color. The brown_lo and brown_hi arrays specify the lower and upper limits for each value, respectively, to define a range of "brown" colors.
- OpenCV is the OpenCV library for Python, which provides various tools for image processing, computer vision, and machine learning. It is a popular and widely-used library for working with images in Python.
- numpy is a package for scientific computing in Python, which provides powerful tools for working with arrays and matrices. It is often used with OpenCV to manipulate and process image data.
This script could help identify objects or features in an aerial image with brownish colors, such as vegetation or buildings made of brown materials. The specific color range used to define "brown" could be adjusted depending on the image and the application.
Here are examples of how to change Brown areas into Red using OpenCV:
Preview of the output that you will get on running this code from your IDE
In this solution we use the Imread function of the OpenCV.
import cv2 as cv
import numpy as np
# Load the aerial image and convert to HSV colourspace
image = cv.imread("aerial.png")
# Define lower and uppper limits of what we call "brown"
# Mask image to only select browns
# Change image to red where we found brown
- Copy the code using the "Copy" button above, and paste it in a Python file in your IDE.
- Import openCv library
- Modify the name, location of the image in the code.
- Run the file to get Output
I hope you found this useful. I have added the link to dependent libraries, version information in the following sections.
i found this code snippet by searching for "change the colors in image with python from specific color range to another color" in kandi. You can try any such use case!
If you do not have OpenCV that is required to run this code, you can install it by clicking on the above link and copying the pip Install command from the OpenCV page in kandi.
You can search for any dependent library on kandi like OpenCV
I tested this solution in the following versions. Be mindful of changes when working with other versions
- The solution is created and executed in python version 3.7.15 .
- The solution is tested on OpenCV 4.6.0
Using this solution, we are going to Change Brown areas into red using OpenCv using the OpenCv library in Python with simple steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us Change Brown areas into red using OpenCv in Python