Weights and Biases Integration

We can also log results directly to your WandB projects. To do this, set project_name to the name of the WandB project where you'd like the results to be logged, and add your WandB API key and entity name to the config dictionary:

config = {
    "wandb_api_key": "YOUR_WANDB_API_KEY",
    "wandb_entity": "your_wandb_entity",
    "leap_api_key": "YOUR_LEAP_API_KEY",
df_results, dict_results = engine.generate(
    class_list=["hotdog", "not_hotdog"],

Hugging Face

We provide a convenvience function to help you download image classification and segmentation directly from Hugging Face. To do this first import the get_model function from from

from import get_model

Then, you can download a model by passing the name of the model to get_model:

preprocessing, model, class_list = get_model("microsoft/resnet-50", source="huggingface")

For more information on the get_model function, see the API Reference.