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Python OpenCV Project – How to Generate Negative Image

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Generating negative images in Python using OpenCV is a crucial task in computer vision and image processing. Negative images, also known as background images, are created by removing the object of interest from a given image, leaving only the surroundings. This process involves loading an image, converting it to grayscale, and then inverting its pixel values to obtain the negative representation. Negative images can be useful for training machine learning models, object detection, and more. In this Python OpenCV How to Generate Negative Images Project, we will explore a step-by-step guide to generating negative images with OpenCV, enabling you to harness the power of computer vision for various applications.

Negative Image

A negative image, in the context of image processing, is the inverse of a positive image. It is created by reversing the brightness values of each pixel, where dark areas become light and vice versa. Negative images are commonly used for various image analysis tasks, emphasizing background or highlighting specific features.

Prerequisites For Python OpenCV How to Generate Negative Images Project

A solid understanding of Python and OpenCV is essential, along with the following system requirements.

  • Python 3.7 (64-bit) and above
  • Any Python editor (VS code, Pycharm,etc.)

Download Python OpenCV How to Generate Negative Images Project

Please download the source code of How to Generate Negative Images Using Python OpenCV Project: Python OpenCV How to Generate Negative Images Project Code.

Installation

Open windows cmd as administrator

1. Install Opencv Library.

pip install opencv-python

Let’s Implement

1. Import the opencv library.

import cv2

2. Read the input image.

image = cv2.imread('img.jpg')

3. It converts input image into grayscale.

gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

4. It inverts the pixel values in a grayscale image, transforming dark areas into light and vice versa. It creates the negative version of the original image.

negative_image = 255 - gray_image

5. It displays original image, negative image and gray image.

cv2.imshow('Original Image By TechVidvan', image)
cv2.imshow('Negative Image By TechVidvan', negative_image)
cv2.imshow('Gray Image By TechVidvan', gray_image)

6. It closes all the windows once the program stops to execute.

cv2.waitKey(0)
cv2.destroyAllWindows(

Python OpenCV How to Generate Negative Images Project Output

Generate Negative Images output

output Generate Negative Images

Generate Negative Images output

Conclusion

In conclusion, this project is a fundamental technique in image processing and computer vision. By inverting pixel values, we create an image where dark becomes light and vice versa, allowing for a stronger emphasis on background or specific features. This process is a crucial preprocessing step for various applications like object recognition. With a solid grasp of Python and OpenCV, you can harness the power of negative images to enhance your image analysis capabilities.

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