Livingwithmachines
/

mr_resnest50d_4s2x40d_timm_pretrain_railspace_and_building

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 # Model Card for mr_resnest50d_4s2x40d_timm_pretrain
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 ## Funding Statement

 # Model Card for mr_resnest50d_4s2x40d_timm_pretrain
+A ResNeSt (ResNet based architecture with Split Attention) image classification model.
+Trained on ImageNet-1k by paper authors and fine-tuned on gold standard annotations and outputs from early experiments using MapReader  (found [here](https://huggingface.co/datasets/Livingwithmachines/MapReader_Data_SIGSPATIAL_2022)).
 ## Model Details
 ### Model Description
+- **Model type:** Image classification /feature backbone
+- **Finetuned from model:**  https://huggingface.co/timm/resnest50d_4s2x40d.in1k
 ## Uses
+This fine-tuned version of the model is an output of the MapReader pipeline. It was used to classify 'patch' images (cells/regions) of scanned nineteenth-century series maps of Britain provided by the National Library of Scotland (learn more [here](https://maps.nls.uk/os/)). We classified patches to indicate the presence of buildings and railway infrastructure. See [our paper](https://dl.acm.org/doi/10.1145/3557919.3565812) for more details about labels.
+## How to Get Started with the Model in MapReader
+Please go to [the MapReader documentation](https://mapreader.readthedocs.io/en/latest/User-guide/Classify.html) for instructions on how to use this model in MapReader.
+## Training, Evaluation and Testing Details
+### Training, Evaluation and Testing Data
+This model was fine-tuned on [manually-annotated data](https://huggingface.co/datasets/Livingwithmachines/MapReader_Data_SIGSPATIAL_2022).
+### Training, Evaluation and Testing Procedure
+Details can be found [here](https://dl.acm.org/doi/10.1145/3557919.3565812).
+Open access version of the article available [here](https://arxiv.org/abs/2111.15592).
 ### Results
+Data outputs can be found [here](https://huggingface.co/datasets/Livingwithmachines/MapReader_Data_SIGSPATIAL_2022).
+Further details can be found [here](https://dl.acm.org/doi/10.1145/3557919.3565812).
+## More Information
+This model was fine-tuned using MapReader.
+The code for MapReader can be found [here](https://github.com/Living-with-machines/MapReader) and the documentation can be found [here](https://mapreader.readthedocs.io/en/latest/).
+## Model Card Authors
+- Katie McDonough (k.mcdonough@lancaster.ac.uk)
+- Rosie Wood (rwood@turing.ac.uk)
 ## Model Card Contact
+Katie McDonough (k.mcdonough@lancaster.ac.uk)
 ## Funding Statement