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: 447 Bytes
436df5c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | # Copyright (c) Facebook, Inc. and its affiliates.
# pyre-unsafe
from .confidence import DensePoseConfidenceModelConfig, DensePoseUVConfidenceType
from .filter import DensePoseDataFilter
from .inference import densepose_inference
from .utils import initialize_module_params
from .build import (
build_densepose_data_filter,
build_densepose_embedder,
build_densepose_head,
build_densepose_losses,
build_densepose_predictor,
)
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