PiSA-Lite is a lightweight, mobile-optimized version of PiSA-SR for Snapdragon-powered smartphones. It is designed to preserve high-quality textures and semantic image details while running through Qualcomm's NPU.
PiSA-Lite is an unofficial optimization based on PiSA-SR. It is not affiliated with or endorsed by the original PiSA-SR authors.
Overview
PiSA-Lite keeps the original PiSA-SR architecture and its semantic image-restoration behavior while preparing the model for mobile deployment.
Unlike small super-resolution models that mainly sharpen edges, PiSA-Lite aims to preserve PiSA-SR's ability to reconstruct material-aware details such as:
wood grain
grass and vegetation
metal reflections
fabric textures
hair and fine surface details
building and object structure
The current release includes:
precompiled Qualcomm QNN Context Binaries for Snapdragon 8 Gen 3
ONNX source models for compiling separate builds for other supported Snapdragon chips
a fixed 4× super-resolution pipeline
an FP16/W8A16 quality configuration
Model Details
Property
Value
Base project
PiSA-SR
Task
Generative image super-resolution
Input
128 × 128 RGB image
Output
512 × 512 RGB image
Upscale factor
4×
Latent shape
1 × 4 × 64 × 64
Target runtime
Qualcomm QNN / HTP NPU
Current target SoC
Snapdragon 8 Gen 3 / SM8650
Current target device family
Samsung Galaxy S24 Family
Deployment format
QNN Context Binary
Source export format
ONNX
Files
Snapdragon 8 Gen 3 QNN Models
The included QNN binaries were compiled specifically for Snapdragon 8 Gen 3 / SM8650:
The ONNX files are source models for creating separate QNN builds for other supported Snapdragon chips:
text
1encoder.onnx
2denoiser.onnx
3decoder.onnx
The ONNX files are not pre-optimized universal mobile models. They must be compiled for the intended Snapdragon target using Qualcomm AI Hub, QAIRT, or another compatible Qualcomm QNN toolchain.
Hardware Compatibility
The supplied .bin files are compiled for:
text
1Qualcomm Snapdragon 8 Gen 3
2SoC: SM8650
3Samsung Galaxy S24 Family
4Android 14
QNN Context Binaries are hardware-specific.
Do not assume that the supplied Snapdragon 8 Gen 3 binaries will work on:
Snapdragon 8 Gen 2
Snapdragon 8 Elite
Snapdragon 7-series devices
Exynos devices
MediaTek devices
desktop CPUs or GPUs
For another supported Snapdragon chip, use the ONNX models to compile a separate QNN package for that target.
Because the complete model package is large, downloading the files after installation is generally preferable to embedding them directly inside the APK.
Compiling for Another Snapdragon Chip
Use the ONNX models as source graphs and compile each component for the selected target device:
A separate set of binaries should be generated for each supported Snapdragon family.
The application should detect the device SoC before downloading or loading a model package.
text
1SM8650 / Snapdragon 8 Gen 3
2→ Load the included SM8650 package
34Another supported Snapdragon chip
5→ Download a separately compiled package
67Unsupported hardware
8→ Use a smaller GPU or CPU fallback model
Intended Use
PiSA-Lite is intended for:
low-resolution photo restoration
experimental mobile photography
restoring vegetation and environmental details
improving material textures
enhancing compressed images
improving game screenshots
research into mobile generative super-resolution
Out-of-Scope Use
PiSA-Lite is not recommended for:
forensic image analysis
identity verification
medical imaging
document or evidence recovery
exact text reconstruction
license-plate recovery
recovering factual details that are not visible in the source image
Limitations
PiSA-Lite is a generative super-resolution model and may create visually plausible details that were not present in the original low-resolution input.
Possible failure cases include:
invented textures
incorrect small text
altered faces
changed logos or symbols
inaccurate fine patterns
unstable results on heavily degraded inputs
high memory use compared with small CNN upscalers
slower inference than models such as SPAN
hardware-specific deployment requirements
Generated output should not be treated as factual evidence.
Current Status
PiSA-SR quality preserved in local testing
Weight-optimized PiSA-Lite package created
ONNX models exported
QNN Context Binaries compiled
Snapdragon 8 Gen 3 NPU inference completed
Public Android runtime example
On-device speed and memory benchmarks
Additional Snapdragon targets
Larger calibration dataset
Hugging Face demo Space
Comparison
Model
Sharpness
Semantic texture reconstruction
Mobile suitability
SPAN
Good
Limited
High
TinySR
Very good
Medium
Medium
PiSA-SR
Very good
Very high
Low
PiSA-Lite
Very good
Very high in current tests
Targeted at Snapdragon NPU
The PiSA-Lite quality claim is based on local visual testing and should be validated on a larger public benchmark set.
Credits
PiSA-Lite is based on the original PiSA-SR project and research.
All credit for the original architecture, training method, pretrained model, and research belongs to the original PiSA-SR authors.
PiSA-Lite focuses on:
mobile deployment
weight optimization
fixed-shape inference
ONNX export
Qualcomm QNN compilation
Snapdragon NPU execution
License and Redistribution
The metadata uses license: other because redistribution rights may depend on multiple upstream components.
Before redistributing model weights or binaries, review and comply with:
the original PiSA-SR license
the Stable Diffusion 2.1 base-model license
all pretrained-model licenses
Qualcomm AI Hub and QNN terms
any checkpoint or dataset restrictions
Uploading this repository does not automatically grant rights beyond the relevant upstream licenses.
Disclaimer
This project is experimental and provided without warranty.
The maintainers are not responsible for:
hallucinated or inaccurate reconstructed details
unsupported-device crashes
excessive memory usage
incorrect Android integration
redistribution outside upstream license terms
damage or data loss caused by use of the model
Use PiSA-Lite at your own risk.
Repository
GitHub:
https://github.com/LoewolfERSTELLER/PiSA-Lite
Short Description
PiSA-Lite is an unofficial, mobile-optimized PiSA-SR upscaler for Snapdragon smartphones, designed to preserve high-quality textures and semantic image details through Qualcomm's NPU.
