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---
library_name: segmentation-models-pytorch
license: mit
pipeline_tag: image-segmentation
tags:
- model_hub_mixin
- pytorch_model_hub_mixin
- segmentation-models-pytorch
- semantic-segmentation
- pytorch
languages:
- python
---
# Unet 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
import albumentations as A
hub_repo = "commaai/comma10k-segnet"
model = smp.from_pretrained(hub_repo)
transform = A.Compose.from_pretrained(hub_repo)
```
## Model init parameters
```python
model_init_params = {
"encoder_name": "tu-efficientnet_b2",
"encoder_depth": 5,
"encoder_weights": None,
"decoder_use_norm": "batchnorm",
"decoder_channels": (256, 128, 64, 32, 16),
"decoder_attention_type": None,
"decoder_interpolation": "nearest",
"in_channels": 3,
"classes": 5,
"activation": None,
"aux_params": None
}
```
## Dataset
Dataset name: comma10k
## 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) |