README.md

metadata

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

DeepLabV3 Model Card

Table of Contents:

• Load trained model
• Model init parameters
• Model metrics
• Dataset

Load trained model

import segmentation_models_pytorch as smp

model = smp.from_pretrained("<save-directory-or-this-repo>")

Model init parameters

model_init_params = {
    "encoder_name": "resnet34",
    "encoder_depth": 5,
    "encoder_weights": "imagenet",
    "decoder_channels": 256,
    "in_channels": 1,
    "classes": 1,
    "activation": None,
    "upsampling": 8,
    "aux_params": None
}

Model metrics

[
    {
        "test_per_image_iou": 0.738848865032196,
        "test_dataset_iou": 0.7336792349815369
    }
]

Dataset

Dataset name: Breast

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