Segment Anything Model (SAM) variants including:
- CoralSCOP
- RepViT-SAM
- EdgeSAM
- MobileSAM
- SAM (original)
combined in the same API (to make life easier).
For more information on different SAM variants, please see the following:
The code requires python>=3.8, as well as pytorch>=1.7 and torchvision>=0.8.
Please follow the instructions here to install both PyTorch and TorchVision
dependencies. Installing both PyTorch and TorchVision with CUDA support is strongly recommended.
Install xSAM:
pip install x-segment-anythingThe SAM models can be loaded in the following ways:
from x_segment_anything import sam_model_registry, SamPredictor
model_type = "vit_b_coralscop"
model_type = "repvit"
model_type = "edge_sam"
model_type = "vit_t"
model_type = "vit_b"
model_type = "vit_l"
model_type = "vit_h"
sam_checkpoint = "path_to_checkpoints/model_x_weights.pt"
device = "cuda" if torch.cuda.is_available() else "cpu"
x_sam = sam_model_registry[model_type](checkpoint=sam_checkpoint)
x_sam.to(device=device)
x_sam.eval()
predictor = SamPredictor(x_sam)
predictor.set_image(<your_image>)
masks, _, _ = predictor.predict(<input_prompts>)or generate masks for an entire image:
from x_segment_anything import SamAutomaticMaskGenerator
mask_generator = SamAutomaticMaskGenerator(x_sam)
masks = mask_generator.generate(<your_image>)For convenience, The following model checkpoints are available in the sam_model_urls dictionary and can be downloaded
in python:
import requests
from x_segment_anything.build_sam import sam_model_urls
def download_asset(asset_url, asset_path):
response = requests.get(asset_url)
with open(asset_path, 'wb') as f:
f.write(response.content)
model_path = "vit_b_coral_scop.pt"
model_path = "repvit.pt"
model_path = "edge_sam.pt"
model_path = "edge_sam_3x.pt"
model_path = "vit_t.pt"
model_path = "vit_b.pt"
model_path = "vit_l.pt"
model_path = "vit_h.pt"
model = model_path.split(".")[0]
model_url = sam_model_urls[model]
download_asset(model_url, model_path)This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an 'as is' basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.
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