To run Smart Prediction with a specific model:
raw_images = sa.search_items( project = "Cityscapes", annotation_status = "NotStarted") succeeded, failed = sa.run_prediction( project = "Cityscapes", images_list = raw_images, model = "Cityscapes Segmentation Model")
This function logs the progress bar which shows the number of images that were predicted successfully.
To download the trained model and its metadata:
sa.download_model( model = "Cityscapes Segmentation Model", output_dir = "./models")
The downloaded model directory contains trained model weights and a configuration file on the model architecture.
Model deployment tutorials
Check out our GitHub repository for model deployment tutorials on edge devices like Jetson Nano and OAK-D.
Updated 7 months ago