GitHub - avidLearnerInProgress/pyCAIR: Content aware image resizing

Readme.md

Content Aware Image Resizing

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Todo:

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• Implement Seam Algorithm
• Generate energy maps and color maps for image
• Display Vertical Seams
• Display Horizontal Seams
• Crop Columns
• Crop Rows
• Use argparse for Command Line Application
• Store subsamples in different directories for crop and seam respectively
• Generate video/gif from sub-samples

Notes:

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Explanation:

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File: notdoneyet.py

• Implemented Seam Carving Algorithm
  • getEnergy() - generated energy map using sobel operators and convolve function.
  • getMaps() - implemented the function to get seams using Dynamic Programming. Also, stored results of minimum seam in seperate list for backtracking.
  • drawSeam() - Plot seams(vertical and horizontal) using red color on image.
  • carve() - reshape and crop image.
• Generated grayscale and energy maps using OpenCV.
  • generateEnergyMap() - utilised OpenCV inbuilt functions for obtaining energies and converting image to grayscale.
  • generateColorMap() - utilised OpenCV inbuilt functions to superimpose heatmaps on the given image.
• Crop Columns
  • cropByColumn() - Implements cropping on both axes, i.e. vertical and horizontal.
  • cropByRow() - Rotate image to ignore repeated computations and provide the rotated image as an input to cropByColumn function.
• Argparse library for user input
  • Parameters:
    • Alignment: Specify on which axis the resizing operation has to be performed.
    • Scale Ratio: Floating point operation between 0 and 1 to scale the output image.
    • Display Seam: If this option isn't selected, the image is only seamed in background. No output for seams is visible.
    • Input Image
    • Generate Sequences: Generate intermediate sequences to form a video after all the operations are performed.
• Helpers
  • writeImage() - stores the images in results directory.
  • writeImageG() - stores intermediate generated sequence of images in sequences directory.
  • createFolder() - self explanatory
  • getFileExtension() - self explanatory

File: imgtovideos.py

• Generate Video
  • _vid() - writes each input image to video buffer for creating a complete video
  • generateVideo() - pass each image path to _vid() for video generation
• Helpers
  • getProcessPaths() - returns list of all sub-directories within a base path with certain conditions.
  • createFolder() - self explanatory

Remaining todos:

1. Implement Object Oriented paradigms
2. Optimize code: Many operations are bruteforce, if there are more better optimized methods; I would love to implement them
3. Implement multithreading wherever possible to improve the computation speed.

In Action:

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• Playlist

Screenshots:

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Results for Image 1:

Original Image Grayscale Energy Map Color Map Winter Color Map Hot Seams for Columns Columns Cropped Seams for Rows Rows Cropped

Results for Image 2:

Original Image Grayscale Energy Map Color Map Winter Color Map Hot Seams for Columns Columns Cropped Seams for Rows Rows Cropped

License:

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This software is licensed under the GNU General Public License v3.0 license