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
File size: 475 Bytes
436df5c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | # Copyright (c) Facebook, Inc. and its affiliates.
from .launch import *
from .train_loop import *
__all__ = [k for k in globals().keys() if not k.startswith("_")]
# prefer to let hooks and defaults live in separate namespaces (therefore not in __all__)
# but still make them available here
from .hooks import *
from .defaults import (
create_ddp_model,
default_argument_parser,
default_setup,
default_writers,
DefaultPredictor,
DefaultTrainer,
)
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