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Commit 27a4c96

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Merge pull request #1068 from Khushi-sharma07/main
Image Neon Effect Filter
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## Neon/Glow Filter Of An Image
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# Aim
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This project helps in converting an image into glow/neon image.
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# Purpose
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In this project a normal RGB image is converted into its neon or glow image using a single script.
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# Short description of package/script
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>This project contains a script neon.py which helps to convert image into neon or glow image.
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>It uses Open CV library to manipulate pixels of the image
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>Numpy is used because Open CV stores images in form of numpy array and it can be manipulated easily by performing numpy operations.
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# Workflow of the Project
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User will enter the name of the file present in the media folder then the program will process the image and convert it into neon/glow image. Then simply the converted file will be created with both the images concattenated for comparision purposes. The new file created will be automatically saved and renamed as "Neon of FILENAME".
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# Detailed Setup instructions
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The first step is to install python and fulfill all the requirements mentioned in requirements.txt. Then copy your images to the Media folder. The extension of image should be .jpg to get the best results.
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After running the program you will get the image converted as per your need and will get saved automatically in the same directory.
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# Compilation Steps
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In this we are using cv2,matplotlib and numpy to read the images and then store it in the form of array. Then with the help of matrix multiplication and setting the pixels properly we get the new image. Then, we finally merge the old and the new image together for better comparision/visualisation purpose and display it and save the image as final output.
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# Conclusion
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This image processing script helps the user to instantly beautify their image and give it a glow by one simple step.
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# Screenshots
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![Image Neon Effect Filter](Media/Screenshot 1)
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![Image Neon Effect Filter](Media/Screenshot 2)
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# Author
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Khushi Sharma
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import cv2
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import numpy as np
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import matplotlib.pyplot as plt
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def main():
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filename = input("Please Enter File Name : ") # Asking Image name
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newfilename = "Media/" + filename # Accessing Image inside "Media" folder
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img = cv2.imread(newfilename)
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param_resize = 2000
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# Resize based on the parameters
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img = cv2.resize(img, (param_resize, param_resize))
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# Gausian
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gaussian = cv2.GaussianBlur(img,(3,3),1)
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# Split the gausian and the orginal image
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b_gaus,g_gaus,r_gaus=cv2.split(gaussian)
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b,g,r=cv2.split(img)
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# Matrix multiplication
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#When reading in with cv2 then the type is uint8, which means the range is max 255
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calculated_b_array = b_gaus.astype(int) + b.astype(int)
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calculated_g_array = g_gaus.astype(int) + g.astype(int)
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calculated_r_array = r_gaus.astype(int) + r.astype(int)
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## If the pixelvalue is higher than 255, set it to 255
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calculated_b_array[calculated_b_array > 255] = 255
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calculated_g_array[calculated_g_array > 255] = 255
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calculated_r_array[calculated_r_array > 255] = 255
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## Merge for visualization purposes
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merged = cv2.merge([calculated_b_array, calculated_g_array, calculated_r_array])
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img2 = np.concatenate((img, merged), axis=1)
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# After doing this write the image to the folder
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cv2.imwrite(f"Neon of {filename}", img2)
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print(f"Neon of {filename} is created") # Display message
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cv2.waitKey(0)
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if __name__ == "__main__":
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main()

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