pymlstudio
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Push model using huggingface_hub.
Browse files- README.md +62 -0
- config.json +15 -0
- model.safetensors +3 -0
README.md
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---
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library_name: segmentation-models-pytorch
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license: mit
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pipeline_tag: image-segmentation
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tags:
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- model_hub_mixin
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- pytorch_model_hub_mixin
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- segmentation-models-pytorch
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- semantic-segmentation
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- pytorch
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languages:
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- python
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---
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# FPN Model Card
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Table of Contents:
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- [Load trained model](#load-trained-model)
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- [Model init parameters](#model-init-parameters)
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- [Model metrics](#model-metrics)
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- [Dataset](#dataset)
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## Load trained model
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```python
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import segmentation_models_pytorch as smp
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model = smp.from_pretrained("<save-directory-or-this-repo>")
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```
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## Model init parameters
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```python
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model_init_params = {
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"encoder_name": "resnet34",
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"encoder_depth": 5,
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"encoder_weights": "imagenet",
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"decoder_pyramid_channels": 256,
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"decoder_segmentation_channels": 128,
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"decoder_merge_policy": "add",
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"decoder_dropout": 0.2,
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"in_channels": 3,
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"classes": 12,
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"activation": None,
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"upsampling": 4,
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"aux_params": None
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}
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```
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## Model metrics
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```json
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{
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"test_per_image_iou": 0.7410496473312378,
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"test_dataset_iou": 0.7378937005996704
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}
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```
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## Dataset
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Dataset name: CamVid
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## More Information
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- Library: https://github.com/qubvel/segmentation_models.pytorch
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- Docs: https://smp.readthedocs.io/en/latest/
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin)
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config.json
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{
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"_model_class": "FPN",
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"activation": null,
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"aux_params": null,
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"classes": 12,
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"decoder_dropout": 0.2,
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"decoder_merge_policy": "add",
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"decoder_pyramid_channels": 256,
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"decoder_segmentation_channels": 128,
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"encoder_depth": 5,
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"encoder_name": "resnet34",
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"encoder_weights": "imagenet",
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"in_channels": 3,
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"upsampling": 4
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:385b5b6b109cd3a4051666bb6d771b843fd652cb443fefe3d5a824c25bed713a
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size 92720000
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