Image Reconstruction using Diffusion Model
The code is not based on any paper. But it does something similar to this paper or (less similar to) this paper.
Before running the code, you should install improved-diffusion package. Check the readme of the improved-diffusion folder. Note: install from my copy, and not from the original repository.
Also models imagenet64_uncond_100M_1500K.pt and upsample_cond_500K.pt need to be downloaded. Links are in the improved-diffusion folder.
To generate 16 samples of doge, run:
python generate.py --model_path imagenet64_uncond_100M_1500K.pt --input_image doge.png --batch_size 16
To upsample these samples from 64 to 256 resolution, run:
python upsample.py --upsample_model_path upsample_cond_500K.pt --lowres_images generated_doge.png.npy --input_image doge.png
Results
The doge image
Turns into this (one of possible outcomes):
As you can see, the model gave doge a body.
The image of myself turned into this (right half of the image was masked off):
As you can see, the model gave me a bird.