See our collection for all versions of SAM.
Run SAM with Keras 3: JAX, PyTorch, or TensorFlow
zeromodels/sam_vit_base
Paper: Segment Anything (arXiv:2304.02643) · HF Papers
SAM (Segment Anything Model) segments whatever you point at. It has no class vocabulary: you give it a prompt (a click or a box) and it returns a mask. A heavy ViT image encoder runs once per image; the prompt encoder and mask decoder are light enough for interactive use.
For more details on the model, please go to Meta's original model card.
Pure-Keras 3 conversion of facebook/sam-vit-base for zeromodels. One implementation runs unmodified on TensorFlow / Torch / JAX.
This is a promptable segmentation checkpoint (SAMPromptableSegment): point (and optional box) prompts, backbone ViT-B.
✨ Quick start
import os
os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
import numpy as np
from PIL import Image
from zeromodels.models.sam import (
SAMPromptableSegment,
SAMProcessor,
)
model = SAMPromptableSegment.from_weights("zeromodels/sam_vit_base")
processor = SAMProcessor.from_weights("zeromodels/sam_vit_base")
image = Image.open("your_image.jpg").convert("RGB")
inputs = processor(
image,
input_points=np.array([[[[450, 200]]]], dtype="float32"),
input_labels=np.array([[[1]]], dtype="int32"),
)
META = ("original_size", "reshaped_size")
output = model({k: v for k, v in inputs.items() if k not in META})
masks = processor.post_process_masks(
output["pred_masks"], original_size=inputs["original_size"]
)
print(output["iou_scores"].shape, masks.shape)
Load any SAM / SAM2 / SAM3 variant the same way with from_weights("zeromodels/<variant>") (use SAMPromptableSegment for this repo):
| Variant | Hub | Family |
|---|---|---|
sam_vit_base | zeromodels/sam_vit_base | SAM |
sam_vit_large | zeromodels/sam_vit_large | SAM |
sam_vit_huge | zeromodels/sam_vit_huge | SAM |
sam2_hiera_small | zeromodels/sam2_hiera_small | SAM2 |
sam2_hiera_base_plus | zeromodels/sam2_hiera_base_plus | SAM2 |
sam2_hiera_large | zeromodels/sam2_hiera_large | SAM2 |
sam3 | zeromodels/sam3 | SAM3 |
Tips
- Set
KERAS_BACKENDbefore importing Keras / zeromodels. - SAM / SAM2: point coordinates are in original pixel space; box prompts need
enable_boxes=True/include_box_input=Truewhen building the graph. - SAM2 in this port is image-only (no video memory bank).
- SAM3: prefer
SAM3InstanceSegment.predict(...)for text prompts; upstreamfacebook/sam3is gated. - See SAM docs and Loading Weights.
- Community / upstream safetensors still work via the
hf:prefix, e.g.SAMPromptableSegment.from_weights("hf:facebook/sam-vit-base").
Special Thanks
A huge thank you to the Meta Segment Anything authors for creating and releasing these models.
License: Apache 2.0.