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Revert "Submission for Model ZOO - HAT models" #226

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7 changes: 1 addition & 6 deletions docs/source/main/model_zoo/MODEL_ZOO.md
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Expand Up @@ -48,12 +48,7 @@ The [Model ZOO](https://chmura.put.poznan.pl/s/2pJk4izRurzQwu3) is a collection
|---------------------------------------------------------------------------------------|------------|--------------------------------------------------------|--------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
|[Residual Dense Network (RDN X2)](https://chmura.put.poznan.pl/s/cLBZpjYn3ubuoii) |64 | Trained on 10 cm/px images set it same as input data | X2 | Model originally trained by H Zhang et. al. in "[A Comparative Study on CNN-Based Single-Image Super-Resolution Techniques for Satellite Images](https://github.com/farahmand-m/satellite-image-super-resolution)" converted to onnx format | [Image](https://chmura.put.poznan.pl/s/Ruz24ZpMNg97joV) from Massachusetts Roads Dataset [Dataset in kaggle](https://www.kaggle.com/datasets/balraj98/massachusetts-roads-dataset) |
|[Residual Dense Network (RDN X4)](https://chmura.put.poznan.pl/s/AaKySmOoOhxW6qZ) |64 | Trained on 10 cm/px images set it same as input data | X4 | Model originally trained by H Zhang et. al. in "[A Comparative Study on CNN-Based Single-Image Super-Resolution Techniques for Satellite Images](https://github.com/farahmand-m/satellite-image-super-resolution)" converted to onnx format | [Image](https://chmura.put.poznan.pl/s/Ruz24ZpMNg97joV) from Massachusetts Roads Dataset [Dataset in kaggle](https://www.kaggle.com/datasets/balraj98/massachusetts-roads-dataset) |
|[Hybrid Attention Transformer (HAT X2)](https://github.com/ArturWoz/HAT-onnx/releases/download/release/HAT_SRx2_ImageNet-pretrain.onnx) |64 | Set it same as input data |X2 |[Model](https://github.com/XPixelGroup/HAT) originally trained by Xiangyu Chen et. al. converted to onnx format | [Image](https://github.com/ArturWoz/HAT-onnx/blob/main/examples/HAT_SRx2_ImageNet-pretrain.onnx.png)|
|[Hybrid Attention Transformer (HAT X3)](https://github.com/ArturWoz/HAT-onnx/releases/download/release/HAT_SRx3_ImageNet-pretrain.onnx) |64 | Set it same as input data |X3 |[Model](https://github.com/XPixelGroup/HAT) originally trained by Xiangyu Chen et. al. converted to onnx format | [Image](https://github.com/ArturWoz/HAT-onnx/blob/main/examples/HAT_SRx3_ImageNet-pretrain.onnx.png)|
|[Hybrid Attention Transformer (HAT X4)](https://github.com/ArturWoz/HAT-onnx/releases/download/release/HAT_SRx4_ImageNet-pretrain.onnx) |64 | Set it same as input data |X4 |[Model](https://github.com/XPixelGroup/HAT) originally trained by Xiangyu Chen et. al. converted to onnx format | [Image](https://github.com/ArturWoz/HAT-onnx/blob/main/examples/HAT_SRx4_ImageNet-pretrain.onnx.png)|
|[Hybrid Attention Transformer - Large (HAT-L X2)](https://github.com/ArturWoz/HAT-onnx/releases/download/release/HAT-L_SRx2_ImageNet-pretrain.onnx) |64 | Set it same as input data |X2 |[Model](https://github.com/XPixelGroup/HAT) originally trained by Xiangyu Chen et. al. converted to onnx format | [Image](https://github.com/ArturWoz/HAT-onnx/blob/main/examples/HAT-L_SRx2_ImageNet-pretrain.onnx.png)|
|[Hybrid Attention Transformer - Large (HAT-L X3)](https://github.com/ArturWoz/HAT-onnx/releases/download/release/HAT-L_SRx3_ImageNet-pretrain.onnx) |64 | Set it same as input data |X3 |[Model](https://github.com/XPixelGroup/HAT) originally trained by Xiangyu Chen et. al. converted to onnx format | [Image](https://github.com/ArturWoz/HAT-onnx/blob/main/examples/HAT-L_SRx3_ImageNet-pretrain.onnx.png)|
|[Hybrid Attention Transformer - Large (HAT-L X4)](https://github.com/ArturWoz/HAT-onnx/releases/download/release/HAT-L_SRx4_ImageNet-pretrain.onnx) |64 | Set it same as input data |X4 |[Model](https://github.com/XPixelGroup/HAT) originally trained by Xiangyu Chen et. al. converted to onnx format | [Image](https://github.com/ArturWoz/HAT-onnx/blob/main/examples/HAT-L_SRx4_ImageNet-pretrain.onnx.png)|

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This line introduces inconsistent formatting with a pipe character followed by no content. This should be removed entirely to maintain a clean table structure. The line should simply be blank (no pipe character).

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