Image Morphing

Image Morphing

This project was focused on creating smooth image transitions using dlib and Delaunay triangulation. Here’s how it works:

1. Tie Point Generation:
   I used dlib to generate corresponding tie points between two images. These points were saved into a .node file, which includes key coordinates that define the features for morphing the images.

2. Triangle Generation:
   The ‘triangle’ executable processes the .node file to create triangles based on the tie points. These triangles are used for the morphing process.

3. Delaunay Triangulation:
   Delaunay’s triangulation algorithm divides the image into triangles, helping to smoothly interpolate between the two images during morphing.

4. Image Interpolation:
   I generated 101 images by gradually varying the alpha parameter from 0 to 1 (in steps of 0.01). Each image represents a different blend between the two source images.

5. GIF Creation:
   The generated images were converted into a GIF using the PIL (Python Imaging Library), with the final result saved as output.gif to show the smooth transition.

Conclusion:

This project was a fun and interesting one to work on. It allowed me to experiment with image processing techniques like Delaunay triangulation and tie point generation, and it was exciting to see the morphing process come to life in the final GIF!