metadata
library_name: transformers
tags:
- image-restoration
- lensless-imaging
license: mit
Lensless Computational Imaging
10 models for reconstructing images from a lensless camera. Trained on DigiCam-Mirflickr-MultiMask-10K.
Models
Classical
| Subfolder | Description |
|---|---|
admm100 |
ADMM, 100 iterations, fixed hyperparameters. |
fista100 |
FISTA, 100 iterations, fixed hyperparameters. |
Unrolled
| Subfolder | Description |
|---|---|
le_admm20 |
ADMM, 20 unrolled steps with learnable per-step hyperparameters. |
le_fista20 |
FISTA, 20 unrolled steps with learnable per-step hyperparameters. |
Modular
| Subfolder | Description |
|---|---|
modular_le_admm5_prepost |
Pre-UNet → 5 ADMM steps → post-UNet. |
modular_le_admm5_pre |
Pre-UNet → 5 ADMM steps. |
modular_le_admm5_post |
5 ADMM steps → post-UNet. |
modular_le_fista5_prepost |
Pre-UNet → 5 FISTA steps → post-UNet. |
GAN super-resolution
| Subfolder | Description |
|---|---|
admm100_bsrgan |
ADMM-100 + pretrained BSRGAN x4. |
admm100_bsrgan_finetune |
ADMM-100 + BSRGAN x4 fine-tuned on DigiCam. |
Usage
from transformers import AutoModel
model = AutoModel.from_pretrained(
"timofeiiz/lensless-computational-imaging",
subfolder="modular_le_admm5_prepost",
trust_remote_code=True,
)
recon = model(lensless, psf)