| license: mit | |
| tags: | |
| - computer-vision | |
| - microscopy | |
| - materials-science | |
| - encoder | |
| - segmentation | |
| - pytorch | |
| - pretrained | |
| library_name: pretrained-microscopy-models | |
| # Pretrained Microscopy Encoder - resnext50_32x4d (imagenet-micronet) | |
| This is a `resnext50_32x4d` encoder pretrained on `imagenet-micronet` microscopy datasets, prepared for use with [segmentation_models.pytorch](https://github.com/qubvel-org/segmentation_models.pytorch). | |
| Models originally pretrained for [pretrained-microscopy-models](https://github.com/nasa/pretrained-microscopy-models) | |
| ## Model Details | |
| - **Architecture**: resnext50_32x4d | |
| - **Pretrained on**: imagenet-micronet | |
| - **Input shape**: RGB images | |
| - **Framework**: PyTorch | |
| - **Use case**: Feature extraction, segmentation backbone | |
| ## Files | |
| - `encoder_weights.pth` - PyTorch `state_dict()` of the encoder | |
| - `README.md` - This model card | |
| - `encoder.py` - Sample code to use the encoder within UNet. | |
| ## License | |
| mit | |