Image Segmentation
Transformers
PyTorch
ONNX
Safetensors
Transformers.js
SegformerForSemanticSegmentation
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Pytorch
vision
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custom_code
Instructions to use briaai/RMBG-1.4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use briaai/RMBG-1.4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="briaai/RMBG-1.4", trust_remote_code=True)# Load model directly from transformers import AutoModelForImageSegmentation model = AutoModelForImageSegmentation.from_pretrained("briaai/RMBG-1.4", trust_remote_code=True, dtype="auto") - Transformers.js
How to use briaai/RMBG-1.4 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-segmentation', 'briaai/RMBG-1.4'); - Notebooks
- Google Colab
- Kaggle
variable = model_input_size ?
#36
by Oyounghyun - opened
guideline had model_input_size
This mean is input picture size ?
If you say yes, I will have a question.
w * h or h * w ?
π€π½ x2 what would be the "model_input_size"?? the total of paramethers, or the total of bites? π€π€π€