Image Segmentation
Transformers
PyTorch
English
garment-mask-generation
image-inpainting
fashion
garment-mask
densepose
human-parsing
Instructions to use Ekliipce/wearit-garment-mask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ekliipce/wearit-garment-mask with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Ekliipce/wearit-garment-mask")# Load model directly from transformers import GarmentMaskPipeline model = GarmentMaskPipeline.from_pretrained("Ekliipce/wearit-garment-mask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Copyright (c) Facebook, Inc. and its affiliates. | |
| # pyre-unsafe | |
| from torch import nn | |
| def initialize_module_params(module: nn.Module) -> None: | |
| for name, param in module.named_parameters(): | |
| if "bias" in name: | |
| nn.init.constant_(param, 0) | |
| elif "weight" in name: | |
| nn.init.kaiming_normal_(param, mode="fan_out", nonlinearity="relu") | |