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. | |
| namespace detectron2 { | |
| int get_cudart_version() { | |
| // Not a ROCM platform: Either HIP is not used, or | |
| // it is used, but platform is not ROCM (i.e. it is CUDA) | |
| return CUDART_VERSION; | |
| int version = 0; | |
| // Create a convention similar to that of CUDA, as assumed by other | |
| // parts of the code. | |
| version = HIP_VERSION_MINOR; | |
| version += (HIP_VERSION_MAJOR * 100); | |
| hipRuntimeGetVersion(&version); | |
| return version; | |
| } | |
| } // namespace detectron2 | |