Image-to-Image
PyTorch
ONNX
TensorRT
English
super-resolution
image-restoration
sisr
real-world-restoration
spandrel
chainner
transformer
attention
Instructions to use Phips/HEART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TensorRT
How to use Phips/HEART with TensorRT:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
examples wording: full-res Real-ESRGAN set
Browse files
README.md
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@@ -165,8 +165,9 @@ All ONNX files are **dynamic-shape fp32, opset 17, onnxslim-optimized**.
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## Visual examples
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`examples/` has
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- `examples/00003_compare.png` (skyline)
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- `examples/ADE_val_00000114_compare.png` (scene)
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## Visual examples
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`examples/` has full-resolution comparisons on the Real-ESRGAN test set (input
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fed as-is), each showing: **input** vs **HEART 4x release** vs **HEART 4x OTF
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fidelity** vs **HEART 4x OTF GAN**.
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- `examples/00003_compare.png` (skyline)
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- `examples/ADE_val_00000114_compare.png` (scene)
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