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upscale-and-refine-models
hugglyberry/upscale-and-refine-models
upscale-and-refine-models is a machine learning model from hugglyberry. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
A curated collection of ONNX models for image upscaling, denoising, deblurring, colorization, segmentation, and other image restoration tasks. All models are in ONNX format for easy cross-platform inference.
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Updated Mar 13, 2026
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At a glance
- License
- other
- Access
- Public
- Created
- Mar 9, 2026
- Updated
- Mar 13, 2026
- SHA
- 4e0cb0e1
Model card
From the Hugging Face model README
Upscale and Refine Models
A curated collection of ONNX models for image upscaling, denoising, deblurring, colorization, segmentation, and other image restoration tasks. All models are in ONNX format for easy cross-platform inference.
Models
Upscaling
| Model | Scale | Description |
|---|---|---|
4xNomosWebPhoto_atd | 4x | High-quality photo upscaler |
SwinIR-4x-GAN | 4x | SwinIR GAN-based upscaler |
SPAN-4x | 4x | Lightweight efficient upscaler |
realcugan-2x-* | 2x | Real-CUGAN variants (conservative, no-denoise, denoise 1x/2x/3x) |
realcugan-3x-* | 3x | Real-CUGAN variants (conservative, denoise 3x) |
realcugan-4x-* | 4x | Real-CUGAN variants (conservative, no-denoise, denoise 3x) |
realesrgan-general-* | 4x | Real-ESRGAN for general photos (fast / plus) |
realesrgan-anime-* | 4x | Real-ESRGAN for anime images (fast / plus) |
Denoising & Artifact Removal
| Model | Description |
|---|---|
1xDeNoise_realplksr_otf | General denoising |
1xDeJPG_realplksr_otf | JPEG artifact removal |
1xDeH264_realplksr | H.264 compression artifact removal |
SCUNet-PSNR | Blind denoising (PSNR-oriented) |
SCUNet-GAN | Blind denoising (GAN-oriented, perceptual) |
dncnn-color-blind | Blind color image denoising |
NAFNet-SIDD-width64 | Real-world denoising |
Deblurring
| Model | Description |
|---|---|
1x-hurrdeblur-superultracompact | Lightweight deblurring |
NAFNet-GoPro-width64 | Motion deblurring (GoPro) |
NAFNet-REDS-width64 | Motion deblurring (REDS) |
maxim-deblurring | MAXIM deblurring |
maxim-deblurring-reds | MAXIM deblurring (REDS) |
maxim-deblurring-realblur-j | MAXIM deblurring (RealBlur-J) |
maxim-deblurring-realblur-r | MAXIM deblurring (RealBlur-R) |
Image Enhancement & Restoration
| Model | Description |
|---|---|
maxim-enhancement | Low-light enhancement |
maxim-retouching | Photo retouching |
maxim-dehazing-indoor | Indoor dehazing |
maxim-dehazing-outdoor | Outdoor dehazing |
maxim-deraining | Deraining |
maxim-deraining-raindrop | Raindrop removal |
maxim-denoising | MAXIM denoising |
Refinement
| Model | Description |
|---|---|
1x-aniscale2-refiner | Anime refinement |
1x-artclarity | Art clarity enhancement |
1x-ghibli-grain | Ghibli-style film grain |
Colorization
| Model | Description |
|---|---|
ddcolor-tiny | DDColor colorization (lightweight) |
ddcolor-large | DDColor colorization (high quality) |
deoldify / deoldify_fp16 | DeOldify colorization (fp32 / fp16) |
deoldify_fixed / deoldify_fp16_fixed | DeOldify with fixes (fp32 / fp16) |
Segmentation & Background Removal
| Model | Description |
|---|---|
RMBG-1.4 | Background removal |
BiRefNet-lite-fp16 | Bilateral reference segmentation (fp16) |
mediapipe-selfie-segmenter | Person segmentation |
mediapipe-multiclass-segmenter | Multi-class segmentation |
Classification
| Model | Description |
|---|---|
anime_real_cls-mobilenetv3 | Anime vs. real photo classifier |
nima-mobilenet-quality | Image quality assessment (NIMA) |
Usage
All models are in ONNX format and can be loaded with any ONNX-compatible runtime:
import onnxruntime as ort
session = ort.InferenceSession("realesrgan-general-plus.onnx")
result = session.run(None, {"input": input_tensor})
License
This repository contains models from multiple open-source projects, each with its own license. See LICENSE for details.
- License
- other
- Created
- Mar 9, 2026
- Updated
- Mar 13, 2026