Image Segmentation
Transformers
Safetensors
sam2
instance-segmentation
panoptic-segmentation
semantic-segmentation
zero-shot
open-vocabulary
beit3
fiftyone
Instructions to use Voxel51/openworld-sam with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Voxel51/openworld-sam with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="Voxel51/openworld-sam")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Voxel51/openworld-sam", dtype="auto") - sam2
How to use Voxel51/openworld-sam with sam2:
# Use SAM2 with images import torch from sam2.sam2_image_predictor import SAM2ImagePredictor predictor = SAM2ImagePredictor.from_pretrained(Voxel51/openworld-sam) with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16): predictor.set_image(<your_image>) masks, _, _ = predictor.predict(<input_prompts>)# Use SAM2 with videos import torch from sam2.sam2_video_predictor import SAM2VideoPredictor predictor = SAM2VideoPredictor.from_pretrained(Voxel51/openworld-sam) with torch.inference_mode(), torch.autocast("cuda", dtype=torch.bfloat16): state = predictor.init_state(<your_video>) # add new prompts and instantly get the output on the same frame frame_idx, object_ids, masks = predictor.add_new_points(state, <your_prompts>): # propagate the prompts to get masklets throughout the video for frame_idx, object_ids, masks in predictor.propagate_in_video(state): ... - Notebooks
- Google Colab
- Kaggle
| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # This source code is licensed under the license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| from setuptools import find_packages, setup | |
| from torch.utils.cpp_extension import BuildExtension, CUDAExtension | |
| def get_extensions(): | |
| srcs = ["sam2/csrc/connected_components.cu"] | |
| compile_args = { | |
| "cxx": [], | |
| "nvcc": [ | |
| "-DCUDA_HAS_FP16=1", | |
| "-D__CUDA_NO_HALF_OPERATORS__", | |
| "-D__CUDA_NO_HALF_CONVERSIONS__", | |
| "-D__CUDA_NO_HALF2_OPERATORS__", | |
| ], | |
| } | |
| ext_modules = [CUDAExtension("sam2._C", srcs, extra_compile_args=compile_args)] | |
| return ext_modules | |
| # Setup configuration | |
| setup( | |
| ext_modules=get_extensions(), | |
| cmdclass={"build_ext": BuildExtension.with_options(no_python_abi_suffix=True)}, | |
| ) | |