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
| from __future__ import absolute_import | |
| from SCHP.networks.AugmentCE2P import resnet101 | |
| __factory = { | |
| 'resnet101': resnet101, | |
| } | |
| def init_model(name, *args, **kwargs): | |
| if name not in __factory.keys(): | |
| raise KeyError("Unknown model arch: {}".format(name)) | |
| return __factory[name](*args, **kwargs) |