Model Details
Full Model IDfinegrain/finegrain-box-segmenter
Pipeline / Taskmask-generation
Libraryrefiners
Downloads (all-time)8.0K
Likes125
Last Modified9/11/2024
Author / Orgfinegrain
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("mask-generation", model="finegrain/finegrain-box-segmenter")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
refinerssafetensorsvisionimage-segmentationmattingremove backgroundbackgroundbackground-removalsalient-object-detectionPyTorchmask-generationdataset:finegrain/finegrain-product-masks-litearxiv:2404.07445license:mitregion:us
More mask-generation Models
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🤖 Task: mask-generation
This model is designed for the mask-generation task. Explore more models for this use case.
All mask-generation Models →📊 Popularity
⬇ Downloads8.0K
❤️ Community Likes125
🛠️ Requirements
- →Install: pip install refiners
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.