Shap-E generates 3D objects conditioned on text or images; this repository contains its code and model release.
Open source
24 alternativessegment-anything (SAM)
Produces high quality object masks from input prompts such as points or boxes, and it can be used to generate masks for all objects in an image.
About segment-anything (SAM)
This is an open-source repository containing code for running inference with the Segment Anything Model (SAM), links for downloading trained checkpoints, and example notebooks. SAM produces object masks from prompts and can generate masks for all objects in an image.
Pricing is not clearly stated.
Key features
- Accept point or box prompts through SamPredictor.
- Generate all-object masks through SamAutomaticMaskGenerator.
- Run command-line mask generation for an image or a folder.
- Export the lightweight mask decoder to ONNX for ONNX runtime environments.
- Offer ViT-H, ViT-L and ViT-B model checkpoints.
- Include example notebooks that show how to use the model.
Best for: Projects that need prompt-based image segmentation in Python.
Watch out for
- Requires Python 3.8 or newer, PyTorch 1.7 or newer, and TorchVision 0.8 or newer.
- A model checkpoint must be downloaded before use.
- CUDA support for PyTorch and TorchVision is strongly recommended.
segment-anything (SAM) at a glance
- Category
- AI & Machine Learning › AI Image Generators
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Details verified
- Oct 22, 2026 · Official source
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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