SAM-CLIP vs. FastSAM: Compared and Contrasted

Models

SAM-CLIP

Use Grounding DINO, Segment Anything, and CLIP to label objects in images.

Learn more about SAM-CLIP

FastSAM

FastSAM is an image segmentation model trained using 2% of the data in the Segment Anything Model SA-1B dataset.

Learn more about FastSAM

Model Type

Instance Segmentation

Model Features

Item 1 Info

Item 2 Info

Architecture

Combination of Segment Anything and CLIP

Frameworks

PyTorch

Annotation Format

Instance Segmentation

GitHub

View Repo

GitHub Stars

7.1k+

License

AGPL-3.0

Paper

View Paper

Training Notebook

Train on Colab

Deploy Model

Deploy with Roboflow

Compare Alternatives

Compare SAM-CLIP and FastSAM with Autodistill

Using Autodistill, you can compare SAM-CLIP and FastSAM on your own images in a few lines of code.

Here is an example comparison:

To start a comparison, first install the required dependencies:


pip install autodistill autodistill-fastsam autodistill-sam-clip

Next, create a new Python file and add the following code:


from autodistill_fastsam import FastSAM
from autodistill_sam_clip import SAMCLIP

from autodistill.detection import CaptionOntology
from autodistill.utils import compare

ontology = CaptionOntology(
    {
        "solar panel": "solar panel",
    }
)

models = [
    FastSAM(ontology=ontology),
    SAMCLIP(ontology=ontology)
]

images = [
    "/home/user/autodistill/solarpanel1.jpg",
    "/home/user/autodistill/solarpanel2.jpg"
]

compare(
    models=models,
    images=images
)

Above, replace the images in the `images` directory with the images you want to use.

The images must be absolute paths.

Then, run the script.

You should see a model comparison like this:

When you have chosen a model that works best for your use case, you can auto label a folder of images using the following code:


base_model.label(
  input_folder="./images",
  output_folder="./dataset",
  extension=".jpg"
)

SAM-CLIP vs. FastSAM

Models

SAM-CLIP

FastSAM

Compare SAM-CLIP and FastSAM with Autodistill

Compare SAM-CLIP vs. FastSAM