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
Upload folder using huggingface_hub
Browse files- upload_fix.py +16 -0
upload_fix.py
ADDED
|
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from huggingface_hub import upload_file
|
| 2 |
+
|
| 3 |
+
# Votre token et username
|
| 4 |
+
username = "Ekliipce" # Changez si nécessaire
|
| 5 |
+
repo_id = f"{username}/wearit-garment-mask"
|
| 6 |
+
|
| 7 |
+
# Upload seulement le fichier corrigé
|
| 8 |
+
upload_file(
|
| 9 |
+
path_or_fileobj="pipeline.py",
|
| 10 |
+
path_in_repo="pipeline.py",
|
| 11 |
+
repo_id=repo_id,
|
| 12 |
+
repo_type="model",
|
| 13 |
+
commit_message="Fix: Remove Pipeline inheritance for standalone usage"
|
| 14 |
+
)
|
| 15 |
+
|
| 16 |
+
print(f"✓ pipeline.py mis à jour sur {repo_id}")
|