LibreQuickSRNetm2-restore
QuickSRNet Medium 2x compact real-time super-resolution, packaged for
LibreYOLO. It has 50,604 parameters and produces an RGB image at twice the
input height and width.
Source
The architecture and official checkpoint come from
quic/aimet-model-zoo
at commit
1bd2bf5b17cdda9251437c444009b29e1a25054b, BSD-3-Clause.
Copyright (c) 2022 Qualcomm Innovation Center, Inc.
The maintained Qualcomm integration was verified against
qualcomm/ai-hub-models
at commit
16dbeb5e2805d4ada7218026de72e36878717d46, BSD-3-Clause.
Official source artifact:
quicksrnet_medium_2x_checkpoint_float32.pth.tar
SHA-256:
a0d176b40a649e45a176c3b53f45e0237015f4f2c17b157ef5c81e38c4442a0d
The model card records DIV2K as the training dataset.
Modifications
The 14 learned state-dict tensors are unchanged. Conversion discards the
training-only epoch, optimizer, PSNR, and SSIM objects, then wraps the tensors
in the LibreYOLO v1.0 checkpoint schema with task=restore, size=m2, and
scale=2. FP32 tensor output matches the pinned upstream implementation
exactly (max_abs_diff == 0).
Converted checkpoint SHA-256:
3f779b461d200704ab82904a110aaa37f41e8258b285e02b7e413b955deb150b
Usage
1from libreyolo import LibreYOLO
2
3model = LibreYOLO("LibreQuickSRNetm2-restore.pt")
4result = model.predict("small.jpg")
5print(result.restore_scale) # 2
6result.save("upscaled.png")
Native PyTorch prediction accepts arbitrary positive image dimensions. Dynamic
spatial ONNX and fixed-canvas TorchScript export are supported.
Reference latency
Synchronized model-forward timings on an NVIDIA GeForce RTX 5070 Ti with
PyTorch 2.11.0 and CUDA 12.8, batch 1, cuDNN benchmarking enabled, 10 warmups,
and 30 timed iterations:
| Input to output | Precision | Median | p95 |
|---|
| 360p to 720p | FP32 | 1.746 ms | 1.770 ms |
| 360p to 720p | FP16 | 0.937 ms | 0.966 ms |
| 720p to 1440p | FP32 | 10.536 ms | 10.931 ms |
| 720p to 1440p | FP16 | 5.437 ms | 5.855 ms |
Image decoding, transfer, and result conversion are excluded.
License
BSD 3-Clause. See
LICENSE and
NOTICE.
