CPU compatible fork of the official SAMv2 implementation.
Features 🚀
- CPU compatible
- ships with config files
- Run image and video inference on CPUs
- Example notebooks showcasing inference using weights and biases.
Installation
You can download it from pypi using pip as follows:
pip install samv2
or from the repository:
pip install git+https://github.com/SauravMaheshkar/samv2.git
Usage
After downloading the official weights, you can use the load_model() helper method to instantiate a model.
from sam2 import load_model
model = load_model(
variant="tiny",
ckpt_path="artifacts/sam2_hiera_tiny.pt",
device="cpu"
)
Example Notebook to run prompted segmentation on images logging predictions as W&B Tables.
Example Notebook to run automatic segmentation on images logging predictions as W&B Tables.
Citation
@article{ravi2024sam2,
title={SAM 2: Segment Anything in Images and Videos},
author={Ravi, Nikhila and Gabeur, Valentin and Hu, Yuan-Ting and Hu, Ronghang and Ryali, Chaitanya and Ma, Tengyu and Khedr, Haitham and R{\"a}dle, Roman and Rolland, Chloe and Gustafson, Laura and Mintun, Eric and Pan, Junting and Alwala, Kalyan Vasudev and Carion, Nicolas and Wu, Chao-Yuan and Girshick, Ross and Doll{\'a}r, Piotr and Feichtenhofer, Christoph},
journal={arXiv preprint},
year={2024}
}
Metadata
Release files for samv2 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| samv2-0.0.4.tar.gz | 59.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| samv2-0.0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 132.6 kB
Release files / samv2-0.0.4.tar.gz
| Download URL | samv2-0.0.4.tar.gz |
|---|---|
| Size | 59.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/5.1.1 CPython/3.10.13
|
Release files / samv2-0.0.4-py3-none-any.whl
| Download URL | samv2-0.0.4-py3-none-any.whl |
|---|---|
| Size | 73.6 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.10.13
|