jiabing24/oxford-pet-segmentation

Unet 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.Unet.from_pretrained("oxford-pet-segmentation")

Model init parameters

model_init_params = {
    "encoder_name": "resnet34",
    "encoder_depth": 5,
    "encoder_weights": "imagenet",
    "decoder_use_batchnorm": True,
    "decoder_channels": (256, 128, 64, 32, 16),
    "decoder_attention_type": None,
    "in_channels": 3,
    "classes": 1,
    "activation": None,
    "aux_params": None
}

Model metrics

[
    {
        "test_per_image_iou": 0.9012773036956787,
        "test_dataset_iou": 0.9069087505340576
    }
]

Dataset

Dataset name: Oxford Pet

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