RF Segment Anything

1.0 verified Sat May 09 auth: no python

RF Segment Anything (rf-segment-anything) provides a simple API to run Meta's Segment Anything Model (SAM) for image segmentation with just a few lines of code. Version 1.0 is currently available. Release cadence is unknown; the library appears to be in early active development.

pip install rf-segment-anything

Common errors

error ModuleNotFoundError: No module named 'rf_segment_anything' ↓

cause Package not installed or installed in a different environment.

fix

Run pip install rf-segment-anything in the correct Python environment.

error AttributeError: module 'rf_segment_anything' has no attribute 'Segmentation' ↓

cause Importing the package instead of the class.

fix

Use from rf_segment_anything import Segmentation.

error RuntimeError: Model vit_h not found. Available: vit_b, vit_l, vit_h ↓

cause Typo in model name or model not downloaded.

fix

Check model name (exact string) and ensure internet connection for first-time download.

Warnings

gotcha Model weights are downloaded automatically on first use to ~/.cache/torch/hub/checkpoints/. Ensure you have disk space and network access. ↓

fix Pre-download weights manually or set environment variable TORCH_HOME to a custom directory.

gotcha The segment() method returns a dictionary with keys 'masks', 'boxes', etc. Do not expect a single mask array; iterate over results. ↓

fix Access result['masks'] for the list of masks.

deprecated The parameter 'model_type' in load_model() may be renamed to 'model_name' in future releases. ↓

fix Use the correct parameter name for your version; check documentation before upgrading.

Imports

Segmentation

wrong

from rf_segment_anything import segment

correct

from rf_segment_anything import Segmentation

The main class is `Segmentation`, not a function named `segment`.

Segmentation
wrong
```
import rf_segment_anything
```
correct
```
from rf_segment_anything import Segmentation
```
Direct import of the package does not expose the class; you must import the class explicitly.

Quickstart

Instantiate a Segmentation object, load a pre-trained model (e.g., vit_h), and call segment() on an image path or numpy array.

from rf_segment_anything import Segmentation

segmenter = Segmentation()
segmenter.load_model("vit_h")

# Use an image path or numpy array
result = segmenter.segment("path/to/image.jpg")
print(result)