ryanfb/torch-warp repository overview

⁠torch-warp

This repository contains a torch implementation for automatically applying optical flow deformations to pairs of images in order to morph between images. The optical flow calculation and loading code is from manuelruder/artistic-videos⁠, and is based on DeepFlow⁠. Theoretically, you could drop in another optical flow program which outputs .flo files in the Middlebury format⁠.

This process is inspired by Patrick Feaster's post on Animating Historical Photographs With Image Morphing⁠.

My blog post about this process: Animating Stereograms with Optical Flow Morphing⁠

⁠Examples

⁠Dependencies

• torch7
• DeepFlow and DeepMatching binaries in the current directory, as deepflow2-static and deepmatching-static

⁠Usage

For input, you need two PNG images of the same dimensions named e.g. filename_0.png and filename_1.png. You can then run ./run-torchwarp.sh filename to run all the steps and output the morphing animation as morphed_filename.gif.

You can also use ./run-stereogranimator.sh ID with an image ID from NYPL's Stereogranimator⁠ to download an animated GIF at low resolution and run it through the morphing process.

If you sign up for the NYPL Digital Collections API⁠, you can use your API token with the included scripts to work with high-resolution original images. The nypl_recrop.rb script takes a Stereogranimator image ID as an argument and reads the API token from the NYPL_API_TOKEN environment variable, and attempts to apply the Stereogranimator's crop values to the original image. The run-stereogranimator-hi-res.sh script uses this process and passes the high-resolution cropped images to run-torchwarp.sh. You can also pass the NYPL_API_TOKEN environment variable in your docker run command⁠.

⁠Docker Usage

I had very little luck getting DeepFlow to work on OS X, so I'm using Docker to run this with the included Dockerfile.

• Build the Docker image with docker build -t torch-warp .
• Run the build with docker run -t -i torch-warp /bin/bash. You may want to map a host directory as a data volume⁠ as well, in order to transfer images back and forth.
• Use the scripts as described above inside the Docker container's shell.

I've also made this repository an automated build on Docker Hub: ryanfb/torch-warp⁠