---
license: bsd-3-clause
library_name: litert
pipeline_tag: image-to-image
tags:
- super-resolution
- real-esrgan
- litert
- tflite
- on-device
- gpu
---

# Real-ESRGAN General x4v3 — LiteRT (CompiledModel GPU)

Real-ESRGAN **realesr-general-x4v3** (SRVGGNetCompact, ~1.2M params, BSD-3-Clause) re-authored to a
**GPU-native** LiteRT `.tflite` via the official **litert_torch** path. ×4 real-world super-resolution.
FP16, **3.5 MB**, input **128×128** → output **512×512** (NHWC, RGB, 0–1).

Verified on a Pixel 8a: the whole graph runs on the GPU delegate (full **LITERT_CL residency**,
211/211 nodes, 1 partition) in **~1 ms**, and the GPU output matches the CPU/PyTorch reference
(corr ≈ 0.995).

## Why this is GPU-clean

A pure CNN, but the stock conversion isn't GPU-clean: **PReLU** lowers to `GREATER`+`SELECT`+`MUL`
and **PixelShuffle** lowers to a >4-D reshape — both GPU-rejected. Here:
- **PReLU → `relu(x) − a·relu(−x)`** (per-channel `a`): exact, only RELU/MUL/SUB.
- **PixelShuffle(4) → a one-hot ConvTranspose(stride 4) → ZeroStuffConvT** (zero-stuff nearest +
  Conv2d): exact, no `TRANSPOSE_CONV`, no >4-D tensors.

Result: **zero GATHER/SELECT/TopK/Cast, no >4-D tensors** — full GPU residency. Re-authored vs
original: corr 1.000000.

## I/O

- **Input** `[1, 128, 128, 3]` NHWC, RGB, **0–1 float** (no mean/std). Tile larger images into
  128×128 patches.
- **Output** `[1, 512, 512, 3]` NHWC, RGB, 0–1 (clamp to [0,1]). ×4 upscale.

## Training data & PII

`realesr-general-x4v3` was trained by the Real-ESRGAN authors on public super-resolution datasets
(DIV2K / Flickr2K / OST and a synthetic high-order degradation pipeline). The model upscales image
pixels only — no faces, identities, or other personal attributes are detected, recognized, or
output. No additional or private data was used; weights are the official release, only the op graph
was re-authored for GPU.

## Sample app + conversion script

Android sample (CompiledModel GPU, before/after compare) and the `litert_torch` conversion script:
https://github.com/google-ai-edge/litert-samples (compiled_model_api/super_resolution)