| --- |
| pipeline_tag: mask-generation |
| license: apache-2.0 |
| base_model: facebook/sam2.1-hiera-base-plus |
| library_name: zeromodels |
| tags: |
| - keras |
| - zeromodels |
| - sam2 |
| - mask-generation |
| - image-segmentation |
| - arxiv:2408.00714 |
| - pytorch |
| - jax |
| - tf |
| --- |
| |
| ## ***See [our collection](https://huggingface.co/collections/zeromodels/sam-v1-v2-v3-6a8eaf73a274fffa2ea83cfd) for all versions of SAM.*** |
|
|
| # Run SAM2 with Keras 3: JAX, PyTorch, or TensorFlow |
|
|
| [](https://github.com/IMvision12/ZeroModels) [](https://imvision12.github.io/ZeroModels/sam2/) [](https://huggingface.co/collections/zeromodels/sam-v1-v2-v3-6a8eaf73a274fffa2ea83cfd) |
|
|
| # zeromodels/sam2_hiera_base_plus |
| |
| Paper: [SAM 2: Segment Anything in Images and Videos (arXiv:2408.00714)](https://arxiv.org/abs/2408.00714) · [HF Papers](https://huggingface.co/papers/2408.00714) |
| |
| SAM2 keeps SAM's promptable formulation and replaces the plain ViT with a Hiera backbone plus FPN neck. This Keras port covers the image path only: point or box prompts on a single image (no video memory / frame propagation). |
| |
| For more details on the model, please go to Meta's original [model card](https://huggingface.co/facebook/sam2.1-hiera-base-plus). |
| |
| Pure-**Keras 3** conversion of [`facebook/sam2.1-hiera-base-plus`](https://huggingface.co/facebook/sam2.1-hiera-base-plus) for [zeromodels](https://github.com/IMvision12/ZeroModels). One implementation runs unmodified on **TensorFlow / Torch / JAX**. |
| |
| This is a **promptable segmentation** checkpoint (`SAM2PromptableSegment`): point (and optional box) prompts, backbone Hiera-B+. |
| |
| ## ✨ Quick start |
| |
| ```python |
| import os |
| os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow" |
|
|
| import numpy as np |
| from PIL import Image |
| from zeromodels.models.sam2 import ( |
| SAM2PromptableSegment, |
| SAM2Processor, |
| ) |
| |
| model = SAM2PromptableSegment.from_weights("zeromodels/sam2_hiera_base_plus") |
| processor = SAM2Processor.from_weights("zeromodels/sam2_hiera_base_plus") |
|
|
| 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 `SAM2PromptableSegment` for this repo): |
|
|
| | Variant | Hub | Family | |
| |---|---|---| |
| | `sam_vit_base` | [`zeromodels/sam_vit_base`](https://huggingface.co/zeromodels/sam_vit_base) | SAM | |
| | `sam_vit_large` | [`zeromodels/sam_vit_large`](https://huggingface.co/zeromodels/sam_vit_large) | SAM | |
| | `sam_vit_huge` | [`zeromodels/sam_vit_huge`](https://huggingface.co/zeromodels/sam_vit_huge) | SAM | |
| | `sam2_hiera_small` | [`zeromodels/sam2_hiera_small`](https://huggingface.co/zeromodels/sam2_hiera_small) | SAM2 | |
| | `sam2_hiera_base_plus` | [`zeromodels/sam2_hiera_base_plus`](https://huggingface.co/zeromodels/sam2_hiera_base_plus) | SAM2 | |
| | `sam2_hiera_large` | [`zeromodels/sam2_hiera_large`](https://huggingface.co/zeromodels/sam2_hiera_large) | SAM2 | |
| | `sam3` | [`zeromodels/sam3`](https://huggingface.co/zeromodels/sam3) | SAM3 | |
|
|
| ## Tips |
|
|
| - Set `KERAS_BACKEND` **before** importing Keras / zeromodels. |
| - SAM / SAM2: point coordinates are in original pixel space; box prompts need `enable_boxes=True` / `include_box_input=True` when building the graph. |
| - SAM2 in this port is image-only (no video memory bank). |
| - SAM3: prefer `SAM3InstanceSegment.predict(...)` for text prompts; upstream `facebook/sam3` is gated. |
| - See [SAM2 docs](https://imvision12.github.io/ZeroModels/sam2/) and [Loading Weights](https://imvision12.github.io/ZeroModels/loading_weights/). |
| - Community / upstream safetensors still work via the `hf:` prefix, e.g. `SAM2PromptableSegment.from_weights("hf:facebook/sam2.1-hiera-base-plus")`. |
|
|
| ## Special Thanks |
|
|
| A huge thank you to the Meta SAM 2 authors for creating and releasing these models. |
|
|
| License: Apache 2.0. |
|
|
