Seam Carving is a content aware image-resizing algorithm where the image is reduced in size by one pixel of height (or width) at a time.
A vertical seam in an image is a path of pixels connected from the top to the bottom with one pixel in each row. A horizontal seam is a path of pixels connected from the left to the right with one pixel in each column.
Steps:
○ Energy Calculation: Each pixel has some RGB values. Calculate energy for each pixel. For ex.- You can use dual-gradient energy function. You can refer to this link for details "https://www.cs.princeton.edu/courses/archive/fall17/cos226/assignments/seam/index.html".
○ Seam Identification: Identify the lowest energy seam.
○ Seam Removal: Remove the lowest energy seam.
Python Script extracts the individual pixel’s RGB values from the image, writes them to rgb_in.txt file and loads them in a 3D Matrix "rgb". Also, it will write RGB values into rgb_out.txt file after successfully applying Seam Carving algorithm from main.cpp file and generate image from the rgb_out.txt file.
Dependencies: Pillow - Python Image Library
Note: Python script is only compatible with Linux Operating System.
How to Run: python3 ./src/driver.py sample1.jpeg
Sample Input (366 x 605):
Sample Output (300 x 400):
