Using Autodistill, you can compare Grounded SAM 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:
Next, create a new Python file and add the following code:
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:
Provide your own image below to test YOLOv8 and YOLOv9 model checkpoints trained on the Microsoft COCO dataset.
COCO can detect 80 common objects, including cats, cell phones, and cars.