To test that the model runs correctly, and to confirm the annotation format, users can pass in the model and
load_predict_fn objects to a test function.
The test function used will vary based on what types of predictions are being returned. The API docs contain all of the supported types in
test_launch_integration.py, but for this guide box annotations will be used since the example model is in that format.
This code can be run both in a Python shell and in a Jupyter notebook.
from nucleus import test_launch_integration test_launch_integration.visualize_box_launch_bundle(img_url, load_predict_fn, model=model, load_model_fn=None, show_image=True)
In a Jupyter notebook,
show_image can be set to
False, but outside that context, it must be set to
True to see the return image.
Updated 5 months ago