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---
library_name: segmentation-models-pytorch
license: mit
pipeline_tag: image-segmentation
tags:
- semantic-segmentation
- pytorch
- segmentation-models-pytorch
languages:
- python
---
# FPN Model Card
Table of Contents:
- [Load trained model](#load-trained-model)
- [Model init parameters](#model-init-parameters)
- [Model metrics](#model-metrics)
- [Dataset](#dataset)
## Load trained model
```python
import segmentation_models_pytorch as smp
model = smp.FPN.from_pretrained("GID-segmentation-FPN_resnet101")
```
## Model init parameters
```python
model_init_params = {
"encoder_name": "resnet101",
"encoder_depth": 5,
"encoder_weights": "imagenet",
"decoder_pyramid_channels": 256,
"decoder_segmentation_channels": 128,
"decoder_merge_policy": "add",
"decoder_dropout": 0.2,
"in_channels": 4,
"classes": 1,
"activation": None,
"upsampling": 4,
"aux_params": None
}
```
## Model metrics
```json
[
{
"test_per_image_iou": 0.6290831565856934,
"test_dataset_iou": 0.7467864155769348
}
]
```
## Dataset
Dataset name: GID
## More Information
- Library: https://github.com/qubvel/segmentation_models.pytorch
- Docs: https://smp.readthedocs.io/en/latest/
This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) |