Auto-Image-Completion

Tool designers and photographers can use it to fill in unwanted or missing parts of images.

1. Interpreting images as samples from a probability distribution.

2. Quickly generating fake images using Generative Adversarial Networks(GANs).

3. Finding the best fake image for image completion.

Technology Stack:

Python
TensorFlow
Pandas
Numpy

To-Do

1. Add screenshots of the work.
2. Train the model on actual human photographs.

Future Scope

Make it auto complete any image(i.e., living as well as non-living)