There are 6 repositories under seam-carving topic.
🌅 Content-aware image resizer and object remover based on Seam Carving algorithm
Content aware image resizing
Seam Carving for Content Aware Image Resizing
Image processing using python and opencv
A numpy implementation of forward energy from the paper “Improved Seam Carving for Video Retargeting" (2008)
A fast Python implementation of Seam Carving for Content-Aware Image Resizing.
Image processing method that allows to remove an object from a photo.
A super-fast Python implementation of seam carving algorithm for intelligent image resizing.
An implementation of the seam carving algorithm, designed to resize images while preventing distortion.
手工实现的智能图片处理系统 包含基础的图片处理功能 各类滤波 seam carving算法 以及结合精细语义分割信息 实现智能去除目标的功能
An image resize tool utilizing seam carving.
Seam Carving Algorithm for content aware image resizing and object removal
Content-Aware Scaling using Seam Carving method with different algorithms for energy mapping
Real time seam carving algorithm implementation
This is my implementation of the simplified version of the seam carving - an algorithm developed by S.Avidan and A.Shamir. Seam carving is an algorithm for 'content-aware' image resizing. The main idea is to resize an image by removing only the least noticeable pixels. I have also made a small web app used to generate interesting results.
OpenDistortBot rewrite in rust
Seam carving (or liquid rescaling) is an algorithm for content-aware image resizing.
A re-implementation of the paper `Rectangling Panoramic Images via Warping`
Implementation of a fast video retargeting method in python.
Distort a video using Seam Carving (video) and Vibrato effect (sound)
Project "SeamCarving" from JetBrainsAcademys Kotlin Developer Track
Implementation of Seam Carving algorithm used to content-aware resizing images.
This Application is developed to make the work of Image Resizing more precise by using the energy function under the domain of Seam Carving Algorithm through Content Aware Image Resizing. There will be no loss of objects or active pixels in the resized image hence the resizing will be lossless in terms of content of the image.