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. | |
| from .base_tracker import ( # noqa | |
| BaseTracker, | |
| build_tracker_head, | |
| TRACKER_HEADS_REGISTRY, | |
| ) | |
| from .bbox_iou_tracker import BBoxIOUTracker # noqa | |
| from .hungarian_tracker import BaseHungarianTracker # noqa | |
| from .iou_weighted_hungarian_bbox_iou_tracker import ( # noqa | |
| IOUWeightedHungarianBBoxIOUTracker, | |
| ) | |
| from .utils import create_prediction_pairs # noqa | |
| from .vanilla_hungarian_bbox_iou_tracker import VanillaHungarianBBoxIOUTracker # noqa | |
| __all__ = [k for k in globals().keys() if not k.startswith("_")] | |