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Water Meter Segmentation

Table of Contents: Load trained model Model init parameters Model metrics Dataset

ArtOtherVersionRevision ae68a66

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124 MB
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vRevision ae68a66
Aktualisiert
27. Sept. 2026
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7
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Bildsegmentierung
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Hugging Face

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Table of Contents: Load trained model Model init parameters Model metrics Dataset

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Hugging FacePrimärVersion ae68a6625ba3aa15ad14aab7a8ecf7f505b2467c
huggingface.co/lanicc/water-meter-segmentation/tree/ae68a6625ba3aa15ad14aab7a8ecf7f505b2467c

Verifiziert 27. Sept.

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model.safetensors

safetensors · 124 MB · SHA-256 46b33928f032…6953 · Hugging Face

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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 model = smp.from_pretrained("<save-directory-or-this-repo>") ``` ## Model init parameters ```python model_init_params = { "encoder_name": "resnet50", "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 ```json [ { "test_per_image_iou": 0.7155967354774475, "test_dataset_iou": 0.6878355741500854 } ] ``` ## Dataset Dataset name: water-meter ## 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)

Source context: 7 downloads · 0 likes · Pipeline image-segmentation · Library segmentation-models-pytorch · Repo lanicc/water-meter-segmentation